{"id":3944233,"url":"https://alion.io/job/remotestar-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":4526839,"name":"RemoteStar","domain":"remotestar.io","url":"https://alion.io/company/remotestar","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Freshteam","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","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":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-11-08T18:10:45Z","employer_posted_date":"2026-11-08","last_verified_at":"2026-11-08T18:10:45Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Location: Bengaluru (Onsite)\nYears of Experience - 2 to 4\nAt RemoteStar, we are hiring for one of our clients - A leader in AI-driven revenue cycle management, transforming medical coding and revenue operations with cutting-edge technology.\nThe company has raised $11 million in total funding from top investors, including Accel and Together Fund.\nJoin us as we scale a cloud-native platform that runs transformer-based Large Language Models rigorously fine-tuned on millions of clinical notes and claims every month. You’ll engineer autonomous coding pipelines that parse ICD-10-CM, CPT® and HCPCS at lightning speed, deliver reimbursement insights with sub-second latency and >99 % accuracy, and tackle the deep-domain challenges that make clinical AI one of the hardest-and most rewarding-problems in tech.\nMachine Learning Engineer - Job Overview\n\n We are seeking a skilled and innovative Machine Learning Engineer with expertise in Natural Language Processing (NLP) and an interest in the latest AI models . This role focuses on driving innovation by introducing non-traditional approaches, deploying scalable models, and implementing advanced AI techniques to solve real-world challenges. The ideal candidate is a strong programmer with a research mindset and the ability to translate the latest advancements in AI into impactful solutions.\nKey Responsibilities:\n\nDevelop, deploy, and maintain ML models and pipelines for NLP tasks.\nDesign and set up self-hosted models for specific tasks, ensuring efficiency and\nscalability.\nEstablish workflows for fine-tuning, feedback loops, and online learning to enhance\nmodel performance.\nImplement and optimise prompt refinement techniques to improve results.\nContinuously research and evaluate state-of-the-art AI advancements to integrate\ninto the organisation's solutions.\nContribute to existing and new projects by:\nStreamlining processes for better estimation and scaling solutions.\nEnhancing testing tools and pipelines for AI development.\nCollaborate with teams to identify opportunities for applying AI and ML to solve\ncomplex problems efficiently.\nBuild and productionize deep learning models, ensuring seamless integration into\nexisting systems.\nRequirements:\nBachelor’s degree in Computer Science, Machine Learning, or a related field.\n2-4 years of experience in machine learning or applied AI roles.\nStrong Python skills with experience in hosting and maintaining ML models at scale.\nProficiency in a deep learning framework (e.g., PyTorch or TensorFlow).\nAbility to explore and evaluate research papers, identifying key methods and\ntechniques for application.\nCapable of combining existing tools and frameworks to create efficient and effective\nsolutions.\nSolid foundation in machine learning principles and statistical techniques.\nStrong communication skills to convey complex ideas to technical and non-technical\nstakeholders.\nPreferred Qualifications:\n\nFamiliarity with cloud platforms, containerization tools (e.g., Docker, Kubernetes),\nand production-level AI workflows.\nExperience working with domain-specific data, such as clinical or biomedical\ndatasets.\nInterest in cutting-edge 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