{"id":1142295,"url":"https://alion.io/job/weekday-machine-learning-engineer-3","title":"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,"is_intermediary":false,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":88,"ghost_share":0,"stale_share":0.977,"repost_share":0,"time_to_fill_p50_days":5,"computed_at":"2026-09-23T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false}],"status":"live","first_seen_at":"2026-09-23T12:49:47Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-09-23T17:32:14Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"This role is for one of Weekday’s clients\nSalary range: Rs 4000000 - Rs 5000000 (ie INR 40 - 50 LPA)\nMin Experience: 3+ years\nLocation: Remote (India)\nJobType: full-time\nWe are looking for a hands-on Machine Learning Engineer to design, develop, deploy, and scale AI/ML systems, with a strong focus on Large Language Models (LLMs), Generative AI, and production-grade AI applications.\nThe ideal candidate will have strong Python engineering skills and experience building AI applications using modern frameworks and infrastructure. This role is suited for someone comfortable working in a fast-paced, high-ownership environment where requirements may evolve quickly and engineers are expected to take broad ownership from experimentation through production deployment.\nYou will work on advanced AI systems involving LLMs, multi-agent architectures, intelligent automation, and real-world business workflows.\nRequirements\nKey Responsibilities\nDesign, develop, and deploy production-grade machine learning and Generative AI applications.\nBuild and integrate LLM-powered applications, intelligent agents, and AI automation workflows.\nDevelop scalable backend services and APIs using Python and FastAPI.\nWork with modern ML frameworks and technologies to develop, evaluate, and improve AI systems.\nDesign and implement AI/ML pipelines covering experimentation, evaluation, deployment, monitoring, and optimization.\nIntegrate foundation models and LLM APIs into production applications.\nBuild reliable AI systems capable of handling complex, multi-step workflows.\nWork with cloud infrastructure and containerized environments to deploy and scale ML applications.\nCollaborate with engineering and product teams to translate business problems into practical AI solutions.\nEvaluate model performance, identify failure modes, and continuously improve accuracy, reliability, latency, and cost.\nContribute to technical architecture decisions across ML systems, APIs, infrastructure, and deployment.\nWork effectively in ambiguous environments and take ownership across the complete development lifecycle.\nTechnical Requirements\nStrong proficiency in Python and experience building production software.\nStrong understanding of Large Language Models (LLMs) and Generative AI.\nHands-on experience with FastAPI or similar Python-based backend frameworks.\nExperience building and deploying production AI/ML applications.\nUnderstanding of machine learning fundamentals, model development, evaluation, and deployment.\nExperience working with APIs, data pipelines, and scalable backend systems.\nStrong software engineering practices, including testing, debugging, version control, and production deployment.\nInfrastructure & ML Stack\nExperience with Kubernetes and containerized application deployment.\nExperience with Google Cloud Platform (GCP) or comparable cloud environments.\nExperience with PyTorch or other modern deep learning frameworks.\nFamiliarity with production ML infrastructure, monitoring, and deployment practices is preferred.\nExperience\n3-5 years of relevant professional experience in Machine Learning, AI Engineering, Software Engineering, or a closely related field.\nDemonstrated experience taking AI/ML solutions from experimentation or prototype through production.\nExperience working on LLM, GenAI, agentic AI, or intelligent automation systems is strongly preferred.\nCandidate Profile\nComfortable working in an early-stage or high-growth environment with broad ownership.\nStrong problem-solving and analytical abilities.\nAble to operate effectively with ambiguity and changing requirements.\nStrong communication and cross-functional collaboration skills.\nDemonstrated ability to take ownership of technical problems and deliver production-ready solutions.\nFounding engineer or startup experience is preferred.\nExperience contributing to published research or open-source LLM/agent projects is a strong plus.\nHealthcare or healthcare-AI domain exposure is beneficial but not mandatory.\nEducation\nA Bachelor's degree in Computer Science, Engineering, Machine Learning, Artificial Intelligence, or a related discipline is preferred.\nEquivalent practical experience, strong production engineering experience, significant open-source contributions, research work, or startup/founding experience may also be considered.\nCandidate Preferences\nGender: No preference.\nNotice Period: Candidates with a notice period of 30-45 days or less are preferred.\nCurrent Industry: No specific current-industry requirement. Candidates from AI, ML, software engineering, SaaS, technology, research, or other relevant domains are welcome.\nAdditional Preferred Criteria\nFounding engineer or startup background with demonstrated ability to take broad ownership.\nPublished research, technical publications, or meaningful open-source contributions in LLMs, GenAI, agents, or machine learning.\nExperience working on complex AI workflows or multi-agent systems.\nExposure to healthcare or other highly regulated domains is an advantage.\nMust-Have Skills\nPython\n Large Language Models (LLMs)\nFastAPI\nMachine Learning\nGenerative AI\nGood-to-Have Skills\nKubernetes\nGCP\n PyTorch\nLLM/Agent Frameworks\nProduction ML Deployment\nMLOps\nOpen-Source AI/ML Contributions\nHealthcare AI","description_format":"text","description_chars":5247,"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":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-23T12:49:47Z"}],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.516,"p_room":1,"age_days":0,"expected_fill_days":5,"reasons":["conf:0","agency","win:early","comp:brand"],"computed_at":"2026-09-23T17:57:59Z"},"pay":null,"html_url":"https://alion.io/job/weekday-machine-learning-engineer-3","json_url":"https://alion.io/job/weekday-machine-learning-engineer-3.json","meta":{"generated_at":"2026-09-23T17:57:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}