{"id":122147,"url":"https://alion.io/job/maxhome-ai-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":6725,"name":"MaxHome.AI","domain":"maxhome.ai","url":"https://alion.io/company/maxhome-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"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":null,"salary_estimate":{"min_usd":24000,"max_usd":51000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Google GKE","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Dagster","optional":true},{"name":"FAISS","optional":true},{"name":"Pinecone","optional":true},{"name":"Prefect","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-08-25T09:04:35Z","employer_posted_date":null,"last_verified_at":"2026-08-25T09:04:35Z","board_verified":false,"closed_at":null,"days_open":52,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":52},"description":"We are looking for a Senior Machine Learning Engineer with 5+ years of industry experience to lead the design, development, and deployment of AI-powered systems. This role combines hands-on ML engineering, backend development, LLM integration, and production-grade infrastructure work. You will work closely with product and engineering teams to build reliable, scalable, and high-impact machine learning features.\nThe candidate will have responsibilities across the following functions:\nMachine Learning and LLMs:\nIntegrate LLMs (OpenAI, Anthropic, etc. ) into pipelines, prompting, workflows, RAG, evaluation, and iteration.\nDesign robust prompt engineering strategies and maintain prompt libraries across environments.\nImprove model performance via fine-tuning, quantisation, pruning, or distillation when needed.\nBuild, train, fine-tune, and optimise ML and LLM-based models for production use cases.\nBackend Engineering:\nDevelop scalable backend systems using Python (FastAPI/Flask preferred).\nArchitect and integrate REST APIs, rate limiting, and monitoring.\nDebug, profile, and optimise API performance in production.\nInfrastructure and DevOps:\nBuild and deploy containerised applications using Docker.\nManage model and service deployments on Kubernetes (EKS, GKE, AKS, or self-managed clusters).\nWork with CI/CD pipelines to ensure smooth releases and automated testing.\nImplement logging, monitoring, and alerting for ML and backend services.\nCollaboration and Leadership:\nWork closely with cross-functional teams to convert business problems into ML solutions.\nProvide technical guidance to junior engineers and contribute to architectural decisions.\nBring a strong bias for shipping, iteration, and maintaining high engineering standards.\nRequirements:\n5+ years of hands-on experience as an ML Engineer or similar role.\nExpert-level Python programming and clean code practices.\nStrong experience designing and integrating production APIs.\nPractical experience integrating LLM models and writing optimised prompts.\nStrong understanding of model fine-tuning, hyperparameter tuning, and inference optimisation.\nExperience with Docker, containerised deployments, and Kubernetes orchestration.\nGood understanding of microservices architecture, distributed systems, and cloud infrastructure.\nSolid problem-solving and debugging skills across the ML lifecycle.\nNice-to-Have:\nExperience with vector databases (Pinecone, Weaviate, FAISS).\nExperience with event-driven architecture (Kafka, Pub/Sub, SQS/SNS).\nExposure to data pipelines (Airflow, Prefect, Dagster).","description_format":"text","description_chars":2565,"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":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["PropTech","Real Estate Brokerage","Real Estate AI"],"lifecycle":[{"event":"open","at":"2026-08-25T09:04:35Z"}],"visa":[],"liveness":{"score":13,"band":"cold","label":"Long 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