{"id":797394,"url":"https://alion.io/job/asapp-lead-machine-learning-engineer-2","title":"Lead Machine Learning Engineer, Evaluations","company":{"id":628,"name":"ASAPP","domain":"asapp.com","url":"https://alion.io/company/asapp","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-14T06:34:16Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States","New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":190000,"currency":"USD","period":"year","gross":null,"usd_annual":190000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-09-11T19:54:30Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-10-14T06:15:10Z","board_verified":true,"closed_at":null,"days_open":32,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":32},"description":"At ASAPP, our mission is simple: deliver the best AI-powered customer experience-faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. ASAPP’s AI Engineering team is seeking an enterprising, talented and curious machine learning engineer.\nThe AI Engineering team is responsible for working closely with the research and modeling teams to create state-of-the-art NLP models for specific tasks,and deploy them in a production setting designed to serve our customers at scale. We are looking for a Machine Learning Engineer to help build and evaluate the core intelligence behind our agentic AI systems. This role will play a key part in designing and owning evaluation frameworks that ensure quality, safety, and performance across complex agentic systems.\nWe're looking for a Lead Machine Learning Engineer to own and grow the evaluation platform that measures quality, safety, and performance across ASAPP's agentic AI systems- the infrastructure that tells us, with confidence, whether a model or agent change is actually an improvement before it reaches customers.\nThisa hybrid role with 10-12 days of in-office presence per month to balance flexibility with collaboration.\nWhat you'll do\nHelp develop the technical roadmap and architecture for the evaluation platform, from offline benchmarking to online/production monitoring of agentic and LLM-based systems.\n\nDesign eval methodologies appropriate to different stages of the pipeline: golden/regression test sets, human-in-the-loop review workflows, LLM-as-judge approaches, and automated metrics for task success, safety, and hallucinations.\n\nBuild the data infrastructure evaluation depends on: annotation and labeling pipelines, dataset versioning, data quality checks, and tooling that lets researchers and product teams run and interpret experiments without needing platform team help.\n\nPartner closely with Research, Product, and Platform teams to productize experiments into robust AI solutions\n\nRepresent the eval platform to stakeholders outside the immediate team- set expectations on what \"good\" looks like for a model/agent release, and report on platform health and coverage.\n\nStay current with advancements in ML, NLP, voice, and LLM systems, and contribute actively to technical discussions across teams.\n\nMentor and support other engineers through design reviews, feedback, and knowledge sharing.\n\nWhat you'll need\nDeep, hands-on experience building and operating evaluation systems for modern ML/LLM/agentic systems- not just consuming existing eval tools.\n\nDemonstrated experience leading the technical direction of a project or small team: setting architecture, driving design reviews, and being accountable for a system's long-term health (not just shipping features).\n\nStrong architectural skills, with proven experience designing complex, data-intensive software systems and production experience with Python, AWS, Kubernetes, and/or Docker.\n\nExperience designing data pipelines for ML evaluation- labeling/annotation workflows, dataset versioning and quality control, and reproducible benchmarking.\n\nA Bachelor’s Degree in CS or other related fields\n\nDemonstrated technical mentorship of junior and mid-level engineers, driving adoption of best practices and architectural alignment for scalability and extensibility.\n\nDesire to learn, teach, and collaborate closely with cross-functional peers.\n\nWhat we'd like to see\nExperience building and evaluating agentic systems at scale.\n\nExperience with voice/audio quality evaluations.\n\nProduction experience with LLM-centric services (e.g., inference, orchestration, evaluation, monitoring)\n\nFamiliarity with large-scale ML experimentation, benchmarking, or simulation frameworks.\n\nExperience with conversational/customer-support AI domains (e.g., containment rate, conversation quality, goal completion).\n\nKnowledge of techniques for optimizing model architectures for faster inference.\n\nExperience with AWS, CI/CD, Kafka, Athena","description_format":"text","description_chars":4107,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Natural Language Processing","Conversational AI","Speech & Audio AI","Contact Center 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