{ "slug": "mem0", "canonical_name": "Mem0", "website": "https://mem0.ai", "ats": "ashby", "top_startup": true, "top_startup_sources": [ "yc" ], "total_active_jobs": 5, "verified_benefits": { "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "source_url": null, "source_label": null, "verified_count": 0, "last_verified": null }, "awards": null, "jobs": [ { "id": "eb8787e20f6f803713f1502e5ff35346", "title": "Applied AI Engineer", "employer_name": "Mem0", "employer_slug": "mem0", "location_text": "San Francisco Bay Area | OnSite", "country": "US", "employment_type": "unknown", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/mem0/0aca5e74-ce97-4186-ad26-6f27e7e21d51", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied AI Engineer San Francisco Bay Area | OnSite Role Summary: Own the 0→1. You'll turn vague customer use cases into working proofs-of-concept that showcase what Mem0 can do. This means rapid full-stack prototyping, stitching together AI tools, and aggressively experimenting with memory retrieval approaches until the use case works end-to-end. You'll partner closely with Research and Backend, communicate trade-offs clearly, and hand off winning prototypes that can be hardened for production. What You'll Do: - Build POCs for real use cases: Stand up end-to-end demos (UI + APIs + data) that integrate Mem0 in the customer's flow. - Experiment with memory retrieval: Try different embeddings, indexing, hybrid search, re-ranking, chunking/windowing, prompts, and caching to hit task-level quality and latency targets. - Prototype with Research: Implement paper ideas and new techniques from scratch, compare baselines, and keep what wins. - Create eval harnesses: Define small gold sets and lightweight metrics to judge POC success; instrument demos with basic telemetry. - Integrate AI tooling: Combine LLMs, vector DBs, Mem0 SDKs/APIs, and third-party services into coherent workflows. - Collaborate tightly: Work with Backend on clean contracts and data models; with Research on hypotheses; share learnings and next steps. - Package & handoff: Write concise docs, scripts, and templates so Engineering can productionize quickly. Minimum Qualifications - Full-stack fluency: Next.js/React on the front end and Python backends (FastAPI/Django/Flask) or Node where needed. - Strong Python and TypeScript/JavaScript; comfortable building APIs, wiring data models, and deploying quick demos. - Hands-on with the LLM/RAG stack:", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": {}, "seniority": "mid", "seniority_source": null, "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": null, "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "seniority": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "role_function": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null } } }, { "id": "b560b1121afe165a9e7c7f745ca2af68", "title": "Founding Technical Recruiter", "employer_name": "Mem0", "employer_slug": "mem0", "location_text": "San Francisco Bay Area | OnSite", "country": "US", "employment_type": "unknown", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/mem0/9cf05288-313e-48a7-a5a5-63f42e6c94e6", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Founding Technical Recruiter San Francisco Bay Area | OnSite About Mem0 We're building the memory layer for AI agents. Think long-term memory that enables AI to remember conversations, learn from interactions, and build context over time. We're already powering millions of AI interactions. We are backed by top-tier investors and are well capitalized. The Role We're looking for a Founding Technical Recruiter to own recruiting from zero to one. This is not a \"fill reqs\" role. You'll work directly with the founders and hiring managers to define what great looks like, build sourcing and interview systems, raise the talent bar, and close exceptional people across engineering, product, design, GTM, and operations. Our ambition is to build a team on the level of the best engineering and product organizations of the last decade. The right person for this role has that same standard internalized - and gets energized, not intimidated, by it. Because we're early, the role will also include some people operations: onboarding, employee experience, internal rituals, and the broader people work that comes with building a company. What You'll Own - Full-cycle recruiting across multiple high-priority roles, from sourcing through close - Strong pipelines for both technical and non-technical hires - Partnering with founders and hiring managers to define role requirements, leveling, interview loops, and hiring bars - Crisp recruiting processes: sourcing, outreach, screening, coordination, feedback, references, offers, closing - Managing and improving our ATS, workflows, dashboards, and recruiting operating cadence - A candidate experience that reflects the quality", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": {}, "seniority": "mid", "seniority_source": null, "years_experience_min": 3, "years_experience_max": 7, "role_function": "hr", "role_function_source": null, "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "seniority": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "role_function": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null } } }, { "id": "8022acfb6198d1b0ed96464519589dcf", "title": "Full Stack Engineer", "employer_name": "Mem0", "employer_slug": "mem0", "location_text": "San Francisco Bay Area | OnSite", "country": "US", "employment_type": "unknown", "remote_status": "onsite", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 5, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/mem0/e3a26e41-7003-49fd-9c21-fa3973553697", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Full Stack Engineer San Francisco Bay Area | OnSite Role Summary: Build the product surface of Mem0 Platform-our memory platform powering LLM apps. You'll own features end-to-end across Next.js and Python, shipping fast without compromising code quality, performance, or reliability. You'll partner with design, research, and customers to turn real problems into elegant, scalable product experiences-and you'll take true ownership of outcomes. What You'll Do: - Ship end-to-end features: Design APIs, build UIs, write backend logic, own data models, and deploy to production. - Build for scale & speed: Optimize latency, caching, and query patterns; keep pages snappy and backends reliable. - Own quality: Write tests, enforce typing/linting, review PRs, and maintain clean, well-documented code. - Collaborate deeply: Work with Design for great UX, with Research to integrate new memory capabilities, and with customers to refine requirements. - Operate what you build: Add observability, set alerts, debug prod issues, and drive continuous improvements. - Lead with product sense: Prioritize ruthlessly, make tradeoffs explicit, and iterate based on data and feedback. - Go beyond your lane: Unblock teams, learn new tools on the fly, and do what it takes to deliver. Minimum Qualifications - Proven experience shipping full-stack web applications at scale using Next.js/React and Python. - Strong Python skills and familiarity with modern web stacks (REST/GraphQL, Postgres, Redis, Celery/queues). - Solid front-end chops: component architecture, state management, forms, accessibility, SSR/ISR. - Track record of owning features E2E: from design docs to rollout and post-launch iteration. - Code quality mindset: testing", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": {}, "seniority": "mid", "seniority_source": null, "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": null, "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "inferred", "verified": false, "label": "Inferred - 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You'll design clean REST APIs, model data across relational and graph stores, and operate services in production. When customers hit issues, you'll chase them down to root cause, ship fixes, and harden the system-while collaborating tightly with frontend and research to deliver fast, reliable features. 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Applied AI Engineer at Mem0 - San Francisco Bay Area | OnSite - Applied AI Engineer San Francisco Bay Area | OnSite Role Summary: Own the 0→1. You'll turn vague customer use cases into working proofs-of-concept that showcase what Mem0 can do. This means rapid full-stack prototyping, stitching together AI tools, and aggressively experimenting with memory retrieval approaches until the use case works end-to-end. You'll partner closely with Research and Backend, communicate trade-offs clearly, and hand off winning prototypes that can be hardened for production. What You'll Do: - Build POCs for real use cases: Stand up end-to-end demos (UI + APIs + data) that integrate Mem0 in the customer's flow. - Experiment with memory retrieval: Try different embeddings, indexing, hybrid search, re-ranking, chunking/windowing, prompts, and caching to hit task-level quality and latency targets. - Prototype with Research: Implement paper ideas and new techniques from scratch, compare baselines, and keep what wins. - Create eval harnesses: Define small gold sets and lightweight metrics to judge POC success; instrument demos with basic telemetry. - Integrate AI tooling: Combine LLMs, vector DBs, Mem0 SDKs/APIs, and third-party services into coherent workflows. - Collaborate tightly: Work with Backend on clean contracts and data models; with Research on hypotheses; share learnings and next steps. - Package & handoff: Write concise docs, scripts, and templates so Engineering can productionize quickly. Minimum Qualifications - Full-stack fluency: Next.js/React on the front end and Python backends (FastAPI/Django/Flask) or Node where needed. - Strong Python and TypeScript/JavaScript; comfortable building APIs, wiring data models, and deploying quick demos. - Hands-on with the LLM/RAG stack:

", "datePosted": "2026-06-10T03:52:15.000Z", "employmentType": "OTHER", "identifier": { "@type": "PropertyValue", "name": "Mem0", "value": "eb8787e20f6f803713f1502e5ff35346" }, "hiringOrganization": { "@type": "Organization", "name": "Mem0" }, "jobLocation": { "@type": "Place", "address": { "@type": "PostalAddress", "addressCountry": "US" } }, "directApply": false, "experienceRequirements": { "@type": "OccupationalExperienceRequirements", "monthsOfExperience": 36 }, "educationRequirements": "no requirements", "url": "https://fewerjobs.com/jobs/mem0/applied-ai-engineer-eb8787e2" } }, { "@type": "ListItem", "position": 2, "url": "https://fewerjobs.com/jobs/mem0/founding-technical-recruiter-b560b112", "item": { "@context": "https://schema.org", "@type": "JobPosting", "title": "Founding Technical Recruiter", "description": "

Founding Technical Recruiter at Mem0 - San Francisco Bay Area | OnSite - Founding Technical Recruiter San Francisco Bay Area | OnSite About Mem0 We're building the memory layer for AI agents. Think long-term memory that enables AI to remember conversations, learn from interactions, and build context over time. We're already powering millions of AI interactions. We are backed by top-tier investors and are well capitalized. The Role We're looking for a Founding Technical Recruiter to own recruiting from zero to one. This is not a "fill reqs" role. You'll work directly with the founders and hiring managers to define what great looks like, build sourcing and interview systems, raise the talent bar, and close exceptional people across engineering, product, design, GTM, and operations. Our ambition is to build a team on the level of the best engineering and product organizations of the last decade. The right person for this role has that same standard internalized - and gets energized, not intimidated, by it. Because we're early, the role will also include some people operations: onboarding, employee experience, internal rituals, and the broader people work that comes with building a company. What You'll Own - Full-cycle recruiting across multiple high-priority roles, from sourcing through close - Strong pipelines for both technical and non-technical hires - Partnering with founders and hiring managers to define role requirements, leveling, interview loops, and hiring bars - Crisp recruiting processes: sourcing, outreach, screening, coordination, feedback, references, offers, closing - Managing and improving our ATS, workflows, dashboards, and recruiting operating cadence - A candidate experience that reflects the quality

", "datePosted": "2026-06-10T03:52:15.000Z", "employmentType": "OTHER", "identifier": { "@type": "PropertyValue", "name": "Mem0", "value": "b560b1121afe165a9e7c7f745ca2af68" }, "hiringOrganization": { "@type": "Organization", "name": "Mem0" }, "jobLocation": { "@type": "Place", "address": { "@type": "PostalAddress", "addressCountry": "US" } }, "directApply": false, "experienceRequirements": { "@type": "OccupationalExperienceRequirements", "monthsOfExperience": 36 }, "educationRequirements": "no requirements", "url": "https://fewerjobs.com/jobs/mem0/founding-technical-recruiter-b560b112" } }, { "@type": "ListItem", "position": 3, "url": "https://fewerjobs.com/jobs/mem0/full-stack-engineer-8022acfb", "item": { "@context": "https://schema.org", "@type": "JobPosting", "title": "Full Stack Engineer", "description": "

Full Stack Engineer at Mem0 - San Francisco Bay Area | OnSite - Full Stack Engineer San Francisco Bay Area | OnSite Role Summary: Build the product surface of Mem0 Platform-our memory platform powering LLM apps. You'll own features end-to-end across Next.js and Python, shipping fast without compromising code quality, performance, or reliability. You'll partner with design, research, and customers to turn real problems into elegant, scalable product experiences-and you'll take true ownership of outcomes. What You'll Do: - Ship end-to-end features: Design APIs, build UIs, write backend logic, own data models, and deploy to production. - Build for scale & speed: Optimize latency, caching, and query patterns; keep pages snappy and backends reliable. - Own quality: Write tests, enforce typing/linting, review PRs, and maintain clean, well-documented code. - Collaborate deeply: Work with Design for great UX, with Research to integrate new memory capabilities, and with customers to refine requirements. - Operate what you build: Add observability, set alerts, debug prod issues, and drive continuous improvements. - Lead with product sense: Prioritize ruthlessly, make tradeoffs explicit, and iterate based on data and feedback. - Go beyond your lane: Unblock teams, learn new tools on the fly, and do what it takes to deliver. Minimum Qualifications - Proven experience shipping full-stack web applications at scale using Next.js/React and Python. - Strong Python skills and familiarity with modern web stacks (REST/GraphQL, Postgres, Redis, Celery/queues). - Solid front-end chops: component architecture, state management, forms, accessibility, SSR/ISR. - Track record of owning features E2E: from design docs to rollout and post-launch iteration. - Code quality mindset: testing

", "datePosted": "2026-06-10T03:52:15.000Z", "employmentType": "OTHER", "identifier": { "@type": "PropertyValue", "name": "Mem0", "value": "8022acfb6198d1b0ed96464519589dcf" }, "hiringOrganization": { "@type": "Organization", "name": "Mem0" }, "jobLocation": { "@type": "Place", "address": { "@type": "PostalAddress", "addressCountry": "US" } }, "directApply": false, "experienceRequirements": { "@type": "OccupationalExperienceRequirements", "monthsOfExperience": 36 }, "educationRequirements": "no requirements", "url": "https://fewerjobs.com/jobs/mem0/full-stack-engineer-8022acfb" } }, { "@type": "ListItem", "position": 4, "url": "https://fewerjobs.com/jobs/mem0/senior-research-engineer-7669e09e", "item": { "@context": "https://schema.org", "@type": "JobPosting", "title": "Senior Research Engineer", "description": "

Senior Research Engineer at Mem0 - San Francisco Bay Area | OnSite - Senior Research Engineer San Francisco Bay Area | OnSite Role Summary: Own the end-to-end lifecycle of memory features-from research to production. You'll fine-tune models for extraction, updates, consolidation/forgetting, and conflict resolution; turn customer pain points into research hypotheses; implement and benchmark ideas from papers; and ship with Engineering to SOTA latency, reliability, and cost. You'll also build evaluation at scale (offline metrics + online A/Bs) and close the loop with real-world feedback to continuously improve quality. What You'll Do: - Fine-tune and train models for memory extraction, updates, consolidation/forgetting, and conflict resolution; iterate based on data and outcomes. - Read, reproduce, and implement research: quickly prototype paper ideas, benchmark against baselines, and productionize what wins. - Build evaluation at scale: automated relevance/accuracy/consistency metrics, gold sets, online A/B & interleaving, and clear dashboards. - Work closely with customers to uncover pain points, turn them into research hypotheses, and validate solutions through field trials. - Partner with Engineering to ship: design APIs and data contracts, plan safe rollouts, and maintain SOTA latency, reliability, and cost at scale. Minimum Qualifications - Experience in RAG or information retrieval (retrieval, ranking, query understanding) for real products. - Model training/fine-tuning experience (LLMs/encoders) with a strong footing in experimental design and iteration. - Strong Python; deep experience with PyTorch and familiarity with vLLM and modern serving frameworks. - Built evaluation for complex vision-and-language tasks (gold sets, offline metrics, online tests). - Able to orchestrate data pipelines to run these models in production with low-latency SLAs (batch +

", "datePosted": "2026-06-10T03:52:15.000Z", "employmentType": "OTHER", "identifier": { "@type": "PropertyValue", "name": "Mem0", "value": "7669e09ed1c56d1485c3bf6f873e1210" }, "hiringOrganization": { "@type": "Organization", "name": "Mem0" }, "jobLocation": { "@type": "Place", "address": { "@type": "PostalAddress", "addressCountry": "US" } }, "directApply": false, "experienceRequirements": { "@type": "OccupationalExperienceRequirements", "monthsOfExperience": 60 }, "educationRequirements": "no requirements", "url": "https://fewerjobs.com/jobs/mem0/senior-research-engineer-7669e09e" } }, { "@type": "ListItem", "position": 5, "url": "https://fewerjobs.com/jobs/mem0/backend-engineer-03db7768", "item": { "@context": "https://schema.org", "@type": "JobPosting", "title": "Backend Engineer", "description": "

Backend Engineer at Mem0 - San Francisco Bay Area | OnSite - Backend Engineer San Francisco Bay Area | OnSite Role Summary: Own the backend that powers Mem0's memory platform. You'll design clean REST APIs, model data across relational and graph stores, and operate services in production. When customers hit issues, you'll chase them down to root cause, ship fixes, and harden the system-while collaborating tightly with frontend and research to deliver fast, reliable features. What You'll Do: - Design & ship REST APIs: Define contracts, versioning, auth, rate limits; write migrations and docs. - Model data & schemas: Relational (Postgres) and graph (e.g., Neo4j); enforce integrity and performance. - Debug customer issues end-to-end: Trace with logs/metrics/traces, reproduce, fix, and write preventative guardrails. - Optimize performance: Tune slow SQL with EXPLAIN/ANALYZE, indexes, partitioning, pagination, and caching (e.g., Redis). - Build services in Python: Async where it helps (FastAPI/Starlette, Django/DRF, Flask), background jobs, queues, schedulers. - Operate in the cloud: Containerize with Docker, deploy on Kubernetes (EKS), and use AWS primitives (EC2, RDS/Aurora, S3, IAM). - Instrument everything: Custom metrics, structured logging, tracing; set SLOs and alerts (CloudWatch/Prometheus/OpenTelemetry). - Collaborate & ship: Work with frontend and research to scope APIs and deliver features to production. Minimum Qualifications - 3+ years building backend systems and shipping REST APIs to production. - Strong Python fundamentals; experience with async programming and a major web framework (FastAPI/Django/Flask). - Solid data modeling and SQL skills; hands-on with query tuning and performance debugging in Postgres/MySQL. - Experience with graph databases (e.g., Neo4j or Amazon Neptune) and appropriate data modeling

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