{"id":1133983,"url":"https://alion.io/job/6sense-sr-machine-learning-engineer-3","title":"Sr. Machine Learning Engineer","company":{"id":2872,"name":"6Sense","domain":"6sense.com","url":"https://alion.io/company/6sense","size_band":"1001-5000","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":10,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-23T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":42000,"max_usd":108000,"period":"year","method":"role_seniority_country_cell","sample_n":10},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Spark","optional":false},{"name":"AWS Bedrock","optional":true},{"name":"Feature Store","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LangSmith","optional":true},{"name":"MLFlow","optional":true},{"name":"RAG","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-09-23T05:04:25Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-09-23T13:23:55Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Our Mission:\n6sense's mission is to multiply what matters: growth, retention, and efficiency. We envision a future where companies, teams and people reach their full potential.\nOur People:\nPeople are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging. Every 6sensor plays a part in defining the future of our industry-leading technology. 6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers. We want 6sense to be the best chapter of your career. \nAbout the Role: \nWe’re hiring a Sr. Machine Learning Engineer to join the ML Engineering team. Our team builds the production systems that make 6sense’s machine learning dependable at massive scale: model-training and refresh pipelines, evaluation and release controls, high-throughput batch and online inference, and the shared platforms that let Data Science and product teams ship safely. \nThis is a hands-on engineering role for someone who enjoys owning the hard middle between a strong model and a reliable customer capability. You will work closely with Data Scientists, platform engineers, and product teams to turn experimentation into governed, observable, scalable production systems. You will help shape how models and AI agents are evaluated, promoted, monitored, and improved-not simply deploy them once. \nWhat You’ll Do :\nOwn production ML capabilities end to end: turn a business or modeling need into a well-designed pipeline or service, then operate and improve it in production. \nBuild and evolve scalable training, model-refresh, feature/data-validation, and inference workflows across batch and real-time use cases. \nDesign reliable model lifecycle controls: experiment tracking, evaluation gates, model/version promotion, rollback, lineage, reproducibility, and monitoring. \nBuild platform primitives that enable Data Science and AI product teams to ship faster without compromising reliability, security, or cost. \nImprove the performance, resilience, and observability of distributed ML workloads and model-serving systems. \nPartner with Data Science on evaluation design, data quality, model-health signals, and production debugging. \nContribute to LLM/agent evaluation and serving infrastructure where appropriate, including offline and online evaluation, tracing, quality gates, and regression detection. \nLead technical design for ambiguous projects, influence architecture across teams, and mentor engineers through code reviews and hands-on guidance. \nCommunicate decisions, risks, and operational status clearly to engineering, product, and leadership stakeholders. \nWhat We’re Looking For :\nRequired : \n6+ years of industry experience building and operating production machine-learning or data-intensive distributed systems, including substantial end-to-end ownership. \nStrong Python engineering skills and practical experience designing maintainable, testable services and pipelines. \nDemonstrated MLOps depth: experiment tracking, model registry/versioning, CI/CD, reproducible training, data/model validation, deployment strategies, rollback, and production monitoring. \nExperience with distributed data and ML infrastructure such as Spark, Ray, Databricks, Kubernetes, AWS, or equivalent platforms. \nStrong understanding of model-training and inference trade-offs: data quality, feature engineering, evaluation, latency/throughput, cost, reliability, and model drift. \nExperience productionizing at least one of: classical ML models, deep-learning/NLP models, embedding/retrieval systems, or LLM/agent workflows. \nSolid judgment in incident response and operational ownership; able to diagnose failures across data, model, infrastructure, and serving layers. \nAbility to translate ambiguous product and Data Science requirements into a pragmatic technical plan and drive it to completion. \nClear written and verbal communication with both technical and non-technical partners. \nNice to Have :\nHands-on experience with MLflow, Databricks, Ray, Kubernetes, Triton/managed model serving, or similar ML platform tooling. \nExperience operating high-volume batch scoring or low-latency online inference systems. \nExperience with LLM/agent evaluation frameworks, tracing/observability, RAG, vector search, LangGraph/LangSmith, or Amazon Bedrock. \nExperience with feature stores, data contracts, schema validation, and data-quality systems. \nExperience in B2B SaaS or a high-scale data platform where reliability and customer impact matter. \nOur Benefits: \nFull-time employees can take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. We’ll make sure you have the equipment and support you need to work and connect with your teams, at home or in one of our offices. \nWe have a growth mindset culture that is represented in all that we do, from onboarding through to numerous learning and development initiatives including access to our LinkedIn Learning platform. Employee well-being is also top of mind for us. We host quarterly wellness education sessions to encourage self care and personal growth. From wellness days to ERG-hosted events, we celebrate and energize all 6sense employees and their backgrounds. \nEqual Opportunity Employer: \n6sense is an Equal Employment Opportunity and Affirmative Action Employers. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to . \nWe are aware of recruiting impersonation attemptsthat are not affiliated with 6sense in any way. All email communications from 6sensewill originate from the @6sense.com domain. We will not initially contact you via text message and will never request payments. If you are uncertain whether you have been contacted by an official 6sense employee, reach out to ","description_format":"text","description_chars":6382,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Parental leave","Stock options"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Sales Enablement","Marketing Automation","Lead Generation","Marketing & Sales AI"],"lifecycle":[{"event":"open","at":"2026-09-23T06:07:33Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":32,"reasons":["conf:1","win:early"],"computed_at":"2026-09-23T15:20:27Z"},"pay":null,"html_url":"https://alion.io/job/6sense-sr-machine-learning-engineer-3","json_url":"https://alion.io/job/6sense-sr-machine-learning-engineer-3.json","meta":{"generated_at":"2026-09-23T15:20:27Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}