Loop jobs

AI/ML Software Engineer 26 Locations posted: Posted Yesterday

Sr. Mechanical Engineer, Control Actuation Systems (CAS) US-AZ-TUCSON-M10 ~ 3360 E Hemisphere Loop ~ BLDG M10 posted: Posted 9 Days Ago

Capital Projects Integrated Product Team Lead (Onsite) US-AZ-TUCSON-M09 ~ 3350 E Hemisphere Loop ~ BLDG M09 posted: Posted 29 Days Ago

Global Ultrasound Hardware Engineering Leader 2 Locations posted: Posted 30+ Days Ago

Senior Electrical Engineer -Computer Aided Designer Engineer (ECAD) US-AZ-TUCSON-M10 ~ 3360 E Hemisphere Loop ~ BLDG M10 posted: Posted 30+ Days Ago

Scientist MUMBAI GENERAL OFFICE posted: Posted 30+ Days Ago

Network Engineer - Mid 2 Locations posted: Posted 2 Days Ago

2026 Raytheon Full Time - Software Engineer I - Tucson, AZ (Hybrid) US-AZ-TUCSON-M10 ~ 3360 E Hemisphere Loop ~ BLDG M10 posted: Posted 2 Days Ago

Junior Finance Manager (m/w/d) 2 Locations posted: Posted Yesterday

Principal Electrical Engineer-Computer Aided Designer Engineer (ECAD) US-AZ-TUCSON-M10 ~ 3360 E Hemisphere Loop ~ BLDG M10 posted: Posted 30+ Days Ago

Data Scientist CINCINNATI GENERAL OFFICES posted: Posted 30+ Days Ago

Tomahawk Modernization Hardware-In-The-Loop (HWIL) Integrated Product Team Lead (IPTL) US-AZ-TUCSON-9030 ~ 9030 S Rita Rd ~ BLDG 9030 posted: Posted 30+ Days Ago

Senior Data Scientist Singapore posted: Posted Today

Senior Principal DeepStrike-Sensor Fuzed Weapon Execution Chief Engineer (Onsite) US-AZ-TUCSON-M09 ~ 3350 E Hemisphere Loop ~ BLDG M09 posted: Posted 30+ Days Ago

Data Scientists - Finance Bellevue, Washington posted: Posted Yesterday

Lead AI Engineer Mexico - Mexico City Lead AI Engineer (Mexico City) Data Solutions Org Hybrid We are looking for a Lead AI Engineer to drive the development of next-generation AI and ML systems at Salesforce. This role owns the design and evolution of intelligent decisioning systems and expands into building a broader agent flywheel (a system of self-improving feedback loops that continuously evaluate, optimize, and evolve agent performance). This role sits on the applied side but requires strong data and systems engineering depth - you will build not just models and agents, but the data pipelines, evaluation loops, and lightweight system scaffolding that allow them to continuously improve in production. You will build production-grade ML models, embed them into agent workflows, and define how agents learn from real-world outcomes. This is a hands-on, high-impact role focused on shipping systems that directly influence agent performance, efficiency, revenue, and customer experience. What You'll Do 1) Build the Agent Flywheel Design and implement feedback loops that enable agents and ML models to self-improve over time Develop systems for: Outcome tracking (e.g., engagement, conversions, resolution quality) Agent evaluation (LLM + deterministic + human-in-the-loop signals) Iterative optimization (prompting, policies, model selection, fine-tuning) Build pipelines that collect and structure agent traces (inputs, tool usage, intermediate steps, outputs) into high-quality training and evaluation datasets Close the loop from production signals → evaluation → model/prompt improvements 2) Develop Production ML & Agent Systems Build and deploy application-specific ML models (classification, ranking, forecasting, recommendation, etc.) Design and implement

Software Development Engineer - Expert Consultant, AGI - Data Services Boston, Massachusetts, USA Amazon seeks an Software Engineering Domain Expert to provide strategic oversight of human-in-the-loop and model-in-the-loop data pipelines that power next-generation AI solutions. This role sits at the intersection of intellectual rigor and technological innovation - blending deep software development expertise with advanced analytical skills to ensure data excellence at every stage of the Model Training pipeline. The Domain Expert owns high-quality data output from end to end, translates training data needs into scalable engineering solutions, and fosters iterative development practices that raise the bar for the entire team. Beyond individual technical contribution, this role builds organizational capability through hands-on mentorship of junior engineers and strategic guidance on data quality standards. The right candidate thrives in ambiguity, brings clarity to difficult problems, and delivers measurable impact on the effectiveness and reliability of AI systems that serve millions of customers. Key job responsibilities • Serve as a trusted domain advisor to cross-functional teams, providing strategic direction and specialized problem-solving support • Champion domain knowledge sharing across multiple channels and teams to maintain data quality excellence and standardization • Drive collaborative efforts with science teams to optimize output of complex data collections in your domain expertise, ensuring data excellence through iterative feedback loops • Foster team excellence through mentorship and motivation of peers and junior team members • Make informed decisions on behalf of our customers, ensuring that selected code meets industry standards, best practices, and specific client needs •

Senior Financial Analyst 2 Locations posted: Posted Yesterday

Principal TPM, Human-in-the-loop AI platform Bellevue, Washington, USA We are the human-in-the-loop AI platform org for the employee HR experience. We combine the scale of AI with the irreplaceable value of human judgment and empathy. Our technology brings automation, speed, context, and consistency. Our people bring judgment, empathy, and relationship. Together, we deliver experiences employees trust during their most important work moments. Our north star is that technology serves HR professionals, never replaces their judgment on decisions that affect employees' lives. As a Principal Technical Program Manager (TPM) on this team, you will lead the delivery of Amazon's most important HR technology programs, building the next generation of AI-powered tools that reduce repetitive administrative burden in HR workflows so HR professionals can focus on high-judgment, high-empathy work. You will also help refine our AI-augmented strategy and own end-to-end execution of programs that reimagine how HR professionals deliver support at Amazon's global scale. Working closely with engineering, product, operations, and HR business leaders, you'll define scope, sequence, and milestones for our highest-impact programs. You'll drive coherence across our intelligent workflow ecosystem, including tools that surface contextual employee information, assist with policy lookups, support HR workflows, and provide natural language analytics. You'll establish evaluation frameworks and own delivery mechanisms that give senior leadership confidence in execution. Your role requires influencing stakeholders across dozens of HR domains and countries, while knowing when to build consensus and when to make the call. You'll de-risk and deliver on our most important and high-impact projects and

Assembly Manufacturing Operator, All Shifts 2 Locations posted: Posted 30+ Days Ago

Principal AI Engineer California - San Francisco; Washington - Seattle; Illinois - Chicago; California - Palo Alto; New York - New York; Washington - Bellevue We are seeking a highly skilled AI Platform Engineer to play a pivotal role in building the next generation of our ML/AI platform that doesn't just support ML models, but powers autonomous AI agents at enterprise scale. This role sits at the intersection of platform infrastructure and agent systems engineering. You'll build and maintain the core infrastructure, CI/CD pipelines, and platform services that underpin our machine learning initiatives and go further in designing the harnesses, sandboxes, and evaluation frameworks that let AI agents be developed, tested, and trusted in production. You'll work on systems that directly impact marketing, sales, service, and product growth verticals across the organization. This isn't a traditional infrastructure role. You should be comfortable wearing multiple hats of software engineering, agent systems design, and evaluation tooling. We're looking for engineers who think in flywheels: build →evaluate → improve → ship → repeat. What You'll Do Agent Harness & Flywheel Engineering Design and build agent harness infrastructure: the scaffolding that wraps LLM calls, manages tool use, handles retries, enforces policy, and feeds results back into iterative improvement loops. Implement agentic loop patterns with multi-turn reasoning, tool orchestration, memory management, and structured output handling as reusable platform primitives Build the agent flywheel: automated pipelines that collect agent traces, surface regressions, route failures to evaluation, and close the loop from production signal back to prompt/model

Computer Scientist - II 2 Locations posted: Posted Yesterday

Lead AI Engineer, Data Solutions California - San Francisco; Washington - Seattle; Illinois - Chicago; New York - New York We are looking for a Lead AI Engineer to build next-generation AI and ML systems at Salesforce. This role focuses on developing intelligent decisioning systems and building an agent flywheel-a system of feedback loops that continuously evaluate, optimize, and improve agent performance over time. This is an applied AI role with strong data and systems ownership. You will build models and agents and the data pipelines and evaluation loops that enable continuous learning in production. What You'll Do Build the Agent Flywheel Design feedback loops that enable agents and ML systems to improve from real-world outcomes Track outcomes (engagement, conversion, quality) and evaluate agent performance Build pipelines that collect and structure agent traces into training and evaluation datasets Drive continuous improvement via prompting, policies, model selection, and fine-tuning Develop ML & Agent Systems Build and deploy ML models (classification, ranking, forecasting, recommendation) Design AI agents that combine LLM reasoning, tool usage, and ML decisioning Implement reusable patterns for multi-step reasoning, tool orchestration, and structured outputs Integrate models and agents into business-critical workflows Own Data & Model Pipelines Design and build scalable data pipelines (batch and near real-time) for training, evaluation, and inference Transform raw interaction data into features, labels, and evaluation datasets Enable continuous retraining and evaluation through tightly coupled data + model pipelines Ensure data quality, consistency, and reliability Evaluation & Experimentation Build offline and online evaluation frameworks Develop

Team Member I Costa Rica - Alajuela posted: Posted Yesterday