{"id":1458986,"url":"https://alion.io/job/weekday-lead-machine-learning-engineer-2","title":"Lead Machine Learning Engineer","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":85,"ghost_share":0,"stale_share":0.976,"repost_share":0,"time_to_fill_p50_days":5,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":5000000,"max":9900000,"currency":"INR","period":"year","gross":null,"usd_annual":103851},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Azure","optional":false},{"name":"Claude","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Llama","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"AWS","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-09-29T11:14:51Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-01T07:40:15Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"This role is for one of Weekday’s clients\nSalary range: Rs 5000000 - Rs 9900000 (ie INR 50 - 99 LPA)\nMin Experience: 10+ years\nLocation: Bengaluru\nJobType: full-time\nRequirements\nKey Responsibilities:\nMachine Learning & Data Science\nDesign, develop, and deploy end-to-end ML solutions at scale.\nBuild and optimize predictive models, recommendation systems, NLP solutions, and deep learning applications.\nDrive the complete data science lifecycle:\nProblem formulation\nData exploration\nFeature engineering\nModel training\nEvaluation\nGenerative AI\nBuild enterprise-grade GenAI applications using:\nOpenAI\nAzure OpenAI\nAnthropic Claude\nLlama\nMistral\nGemini\nDesign and implement:\nRAG architectures\nAgentic AI systems\nMulti-agent frameworks\nPrompt engineering strategies\nFine-tuning pipelines\nKey Responsibilities:\nDesign, build, deploy, and monitor production-grade ML solutions\nDevelop AI/ML applications using modern ML and GenAI frameworks\nBuild and optimize end-to-end ML pipelines\nCollaborate with Product and Engineering teams to deliver business impact\nDrive best practices in MLOps, model governance, and scalability\nPreferred Skills:\nPython, SQL, Spark\nML/DL frameworks (PyTorch, TensorFlow, Scikit-learn)\nLLMs, RAG, Agentic AI\nDocker, Kubernetes, Cloud Platforms (AWS/Azure/GCP)\nMLOps and model deployment\nProduction deployment\nExcellent communication skills and ability to work with diverse stakeholders\nWhat Sets You Apart:\nExperience optimizing LLMs for production (cost, latency, scaling)\nTrack record of maintaining AI systems in production\nAbility to balance innovation with practical business needs\nExperience with HR/people analytics domain\nMust-have skills\nMachine Learning, GENAI, Production\nGood-to-have skills\nGen AI","description_format":"text","description_chars":1731,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-29T11:14:51Z"}],"liveness":{"score":32,"band":"fade","label":"Fading","p_open":1,"p_active":0.35,"p_room":0.9,"age_days":1,"expected_fill_days":5,"reasons":["conf:6","agency","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":103851,"is_top_pay":false},"html_url":"https://alion.io/job/weekday-lead-machine-learning-engineer-2","json_url":"https://alion.io/job/weekday-lead-machine-learning-engineer-2.json","meta":{"generated_at":"2026-10-01T09:55:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":805,"day_limit":5000,"remaining_today":4195,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}