{"id":2911695,"url":"https://alion.io/job/sparkinity-ml-engineer","title":"ML Engineer","company":{"id":721699,"name":"Sparkinity","domain":"sparkinity.com","url":"https://alion.io/company/sparkinity","size_band":null,"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":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_board_market","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":11500,"max_usd":32000,"period":"year","method":"role_seniority_country_cell","sample_n":17},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Accelerate","optional":false},{"name":"Computer Vision","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-10-20T09:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-20T09:35:00Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We are seeking a Machine Learning Engineer with 3+ years of experience to design, deploy, and scale advanced NLP and computer vision models. If you excel at turning unstructured document data into production-ready AI solutions, we want to hear from you.\n\nResponsibilities: \nDesign, develop, and deploy ML models for document intelligence, content processing, and automated information extraction.\nBuild end-to-end ML pipelines for processing unstructured text, images, scanned documents, and PDFs.\nDevelop and improve NLP and CV solutions for document classification, entity extraction, semantic search, and document understanding.\nExperiment with deep learning architectures, Transformers, and LLM-based approaches to solve real-world document processing challenges.\nConvert research prototypes and experimental models into reliable, scalable, production-ready systems.\nEvaluate model performance using appropriate metrics, statistical analysis, benchmarking, and error analysis.\nOptimize model accuracy, inference speed, scalability, and resource utilization for production workloads.\nBuild and maintain REST APIs and integrate ML models into existing product workflows.\nOwn the deployment of production ML systems that redefine document infrastructure.\nDrive immediate product impact with $6.5M in Series A backing.\nAccelerate your career in a high-growth, remote-first engineering culture.\nCollaborate daily with a world-class, ambitious team of builders.\n\nRequirements: \n3+ years of hands-on experience in machine learning engineering, with a strong focus on computer vision, NLP, or document intelligence.\nStrong proficiency in Python, with experience writing production-quality, maintainable code.\nPractical experience building, training, evaluating, and deploying machine learning and deep learning models.\nStrong understanding of deep learning architectures, including CNNs and Transformers, along with fundamental ML algorithms, mathematics, and statistics.\nExperience with PyTorch and the Hugging Face Transformers ecosystem.\nHands-on experience with unstructured text and document data, including text 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