Member of Technical Staff (Machine Learning Engineer)

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff (Machine Learning Engineer) Remote What You'll Do - Translate cutting-edge research into production-ready machine learning systems - Design, build, and deploy end-to-end ML models and pipelines - Develop and optimize models for image and video processing - Own the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deployment - Rapidly prototype using open-source models and adapt them for product needs - Conduct experiments, analyze results, and iterate to improve performance - Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale - Participate with advancements in machine learning and apply them to continuously improve products What We're Looking For Required Qualifications - MS/PhD in Computer Science, Electrical Engineering, or related field - Strong research experience with familiarity in top conferences (e.g., CVPR, ICCV, NeurIPS) - 5+ years of experience in Python and proficiency in Java, C++, or Scala - Strong understanding of diffusion models - Strong understanding of multi-threading and memory management - Solid knowledge of ML architectures: CNNs and Transformers - Experience with PyTorch or TensorFlow - Experience building end-to-end ML deployment and inference systems, especially for low-latency, real-time applications - Experience deploying ML models in cloud environments (AWS preferred) - Experience with experiment tracking systems and ML workflows Nice to Have - Experience in low level optimisation, cuda etc. - Experience productionizing and scaling ML models in real-world systems - Contributions to open-source projects - Experience with MLOps tools or distributed training systems - Familiarity with relational databases (Postgres/MySQL) -

Read the full description at jobs.ashbyhq.com. FewerJobs shows a preview and links to the original posting.