{"id":122146,"url":"https://alion.io/job/maxhome-ai-machine-learning-engineer-voice-ai","title":"Machine Learning Engineer - Voice AI","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":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":3,"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":"Speech Recognition","optional":false},{"name":"Text-to-Speech","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":"2026-08-25T08:39:35Z","employer_posted_date":null,"last_verified_at":"2026-08-25T08:39:35Z","board_verified":false,"closed_at":null,"days_open":59,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":59},"description":"We're looking for a Senior Machine Learning Engineer (3 to 6 years) 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.\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.\nArchitect and develop Voice AI systems using technologies such as ASR, TTS, LLMs, and conversational AI.\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:\n3 to 6 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":2516,"description_truncated":false,"requirements":{"experience_years_min":3,"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":"2026-08-25T08:39:35Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long 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