{"id":3101739,"url":"https://alion.io/job/datanimbus-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":7501,"name":"DataNimbus","domain":"datanimbus.com","url":"https://alion.io/company/datanimbus","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":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":44000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"Gensim","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLTK","optional":false},{"name":"Pandas","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Databricks","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-22T17:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-22T17:35:00Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"We are looking for experienced Senior Machine Learning Engineers and ML Architects to design, build, and deploy scalable AI/ML solutions that solve complex business problems. In this role, you will work on enterprise-grade data platforms, develop production-ready machine learning and Generative AI applications, and help shape the future of AI-driven products. If you're passionate about Machine Learning, MLOps, Large Language Models (LLMs), and building intelligent systems at scale, we'd love to hear from you.\n\nResponsibilities: \nDesign, develop, and deploy production-grade machine learning solutions across diverse business domains.\nBuild and optimise enterprise AI applications using Large Language Models (LLMs) and Generative AI.\nDevelop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories.\nBuild natural language interfaces for querying structured and unstructured enterprise data.\nApply MLOps best practices to automate model deployment, monitoring, versioning, and lifecycle management.\nCollaborate with cross-functional teams to deliver scalable, high-performance AI solutions.\nProvide technical guidance on AI/ML architecture, tooling, and best practices.\nEnsure reliability, scalability, and performance of ML models in production environments.\n\nRequirements: \nSenior ML Engineer: 4+ years of relevant industry experience.\nML Architect: 6+ years of relevant industry experience.\nStrong proficiency in Python and the AI/ML ecosystem.\nHands-on experience with Pandas, Scikit-learn, MLflow, Gensim, NLTK, TensorFlow, or PyTorch.\nExperience building and deploying production-grade ML solutions on AWS, Azure, or Google Cloud Platform.\nPractical experience with MLOps, including model deployment, monitoring, and drift detection.\nStrong understanding of Machine Learning algorithms, data science workflows, and model evaluation techniques.\nExperience developing LLM-based applications, including Prompt Engineering, RAG, embeddings, and enterprise AI use cases.\nExcellent problem-solving, communication, and collaboration skills.\n\nPreferred Qualifications: \nExperience with Apache Spark for large-scale distributed data processing.\nHands-on experience with Databricks.\nExperience building enterprise AI applications using LLMs and Generative AI frameworks.\nMaster's degree or higher 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