{"id":3576606,"url":"https://alion.io/job/raydar-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":4478753,"name":"Raydar","domain":"raydar.com","url":"https://alion.io/company/raydar-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["GB","CA"],"hiring_countries_total":2,"salary":{"min":250000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Quantization","optional":false},{"name":"Rust","optional":false}],"status":"live","first_seen_at":"2026-10-29T00:00:00Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-02T23:15:45Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About the company\nOur client is a software company.\nThe role\nRaydar is recruiting for this role on behalf of our client. Own the path that takes trained machine learning models into reliable production serving, with a focus on speed, efficiency and dependability at high request volume. The work combines performance tuning of models and GPU-based code with the design of distributed serving systems that run across many machines.\nWhat you'll do\n- Optimize serving latency and throughput for machine learning models.\n- Take models from research through containerization and into stable production deployment.\n- Profile and tune code to make efficient use of GPU hardware.\n- Design and run distributed serving systems across multiple GPUs and nodes.\n- Apply model acceleration methods such as quantization, batching and caching.\nRequirements\nWhat we're looking for\n- Senior-level experience, comparable to a senior software or inference engineer at a large technology company.\n- Track record of developing server-side or learning-based software and getting it running live for real users.\n- Hands-on experience with machine learning inference optimization frameworks.\n- Proficiency in systems programming and GPU optimization in languages such as C++, CUDA, Rust or optimized Python.\n- Familiarity with methods that speed up and shrink models, such as weight compression, knowledge transfer between models or token prediction.\n- Experience with distributed systems, container orchestration and handling high concurrency.\n- Based in an eligible country for this remote role.\nBonus points\n- Public technical work, such as open-source contributions to inference engines or detailed technical write-ups.\n- A history of internal progression and promotions within one employer.\n- A doctorate in a quantitative field, or equivalent hands-on systems experience, with study at a leading university as a further advantage.\nBenefits\nCompensation and benefits\n- Base salary: $250K to $300K\n- Equity\n- Annual performance bonus\n- Health, dental and vision coverage\n- Flexible time off\n- 401(k) retirement plan\n- Health savings account\nLocation and work model\n- Remote (Canada or UK)\n- 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