{"id":3801155,"url":"https://alion.io/job/encord-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":557,"name":"Encord","domain":"encord.com","url":"https://alion.io/company/encord","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"UiPath","optional":true}],"status":"live","first_seen_at":"2026-11-02T14:47:38Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-07T16:38:07Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About us\nEncord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.\nWe're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.\nThe role\nWe're looking for a Senior ML Systems Engineer to join Encord's in-house ML team. This is a software-engineering-first role for someone with real machine learning deployment experience: you'll design, build and run the infrastructure that serves our computer vision and multimodal models in production.\nOur platform is moving from manual, GUI-heavy annotation towards ML-driven workflows, where models do more of the work and learn from annotator feedback. Your job is to make that possible by turning our models into fast, dependable product features.\nOur ML team covers both research and engineering, and this role sits firmly on the engineering side. You'll own architecture, implementation, deployment and production operations, while teammates on the research side focus on longer-horizon experiments and prototypes. Day-to-day, you'll work closely with them, as well as with our Product Engineering and Human Data teams.\nProblems you'll work on\nInteractive inference in the annotation editor. Serving heavy vision and multimodal models fast enough that annotators get model suggestions in real time, with their corrections flowing back as feedback.\n\nInference at very large scale. Pre-computing model outputs across millions of hours of egocentric video for robotics customers, where throughput, GPU cost and reliability all matter.\n\nTaking agentic QC to production. Turning quality-control agents that check multimodal outputs against a customer's ontology from a research prototype into a dependable platform feature.\n\nOne integration, many workflows. Building model integrations that hold up across customers' custom, fast-changing ontologies and task templates, instead of one-off implementations.\n\nWhat you'll do\nDesign, build and operate model-serving and inference infrastructure for transformer-based vision and multimodal models\n\nOwn the serving architecture behind our ML features, justifying trade-offs in latency, throughput, reliability and GPU cost\n\nOptimise models and pipelines for production through batching, KV caching, GPU utilisation and orchestration\n\nIntegrate models into Encord's product and annotation workflows together with Product Engineering\n\nBuild reusable abstractions that work across models, data types, customers and changing task templates\n\nSet up monitoring and observability, and own performance and reliability once features are live\n\nTake prototypes from your research-focused teammates and turn them into shipped features\n\nContribute to platform design decisions, take part in design reviews and help us hire\n\nWork with Python, PyTorch, CUDA, Kubernetes and GCP/AWS\n\nWho we're looking for\nAn owner. You take ambiguous product needs, make the architecture calls and carry the work all the way into production.\n\nA systems thinker. You design for scale and reuse, and you know when a simple, solid baseline beats a clever solution.\n\nA great collaborator. You enjoy working across research, product and engineering, and you make it easier for everyone to ship.\n\nA bridge between research and production. You speak both languages, help researchers get their work shipped, and feed production lessons back into how models are built.\n\nExperience requirements\n5+ years of software engineering experience, including meaningful time building and operating ML systems or model-backed products in production at scale\n\nStrong software engineering and system design fundamentals\n\nHands-on experience deploying modern deep learning models in production, with a strong understanding of model serving, inference optimisation, GPU utilisation and performance trade-offs.\n\nExperience designing and operating scalable, distributed production systems, ideally involving GPU workloads, high-throughput data processing or low-latency inference.\n\nThe ability to reason through an ML system end to end, from data and model choices to offline and online evaluation, deployment, monitoring and retraining\n\nA track record of personally owning complex systems from design through to production\n\nBonus: computer vision or multimodal deployment experience (not required), model-serving frameworks, or experience with video, 3D or other complex data types\n\nWhy Encord\nCompetitive salary and meaningful equity in a high-growth startup\n\nStrong in-person culture - most of the team works from our London office 4+ days/week\n\n25 days annual leave + UK public holidays\n\nAnnual learning & development budget\n\nTravel for customer visits, events, and conferences across the UK and Europe\n\nDaily company lunches\n\nMonthly socials & bi-annual team offsites","description_format":"text","description_chars":5034,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Annual leave","Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["MLOps","AI Training Data & Annotation"],"lifecycle":[{"event":"open","at":"2026-11-05T11:32:21Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":69,"reasons":["conf:0","velocity","win:early"],"computed_at":"2026-11-07T05:47:08Z"},"pay":null,"html_url":"https://alion.io/job/encord-senior-machine-learning-engineer","json_url":"https://alion.io/job/encord-senior-machine-learning-engineer.json","meta":{"generated_at":"2026-11-07T18:20:11Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":27665,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-08T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":557},"rest":"https://alion.io/mcp/rest/get_company?id=557"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fencord-senior-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fencord-senior-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fencord-senior-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/encord-senior-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fencord-senior-machine-learning-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3801155}},{"tool":"search_jobs","arguments":{"company":"encord.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3801155},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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