{"id":2975173,"url":"https://alion.io/job/fugentex-solutions-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":3806667,"name":"FuGenTex Solutions","domain":"fugentex.com","url":"https://alion.io/company/fugentex-solutions","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"WP Job Openings","truth_index":{"grade":"D","score":54,"open_postings":119,"ghost_share":0.773,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"freelance","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":38000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":8},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false},{"name":"Agile","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Computer Vision","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"ETL/ELT","optional":true},{"name":"FAISS","optional":true},{"name":"Kubeflow","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Milvus","optional":true},{"name":"MLFlow","optional":true},{"name":"NLP","optional":true},{"name":"Pinecone","optional":true},{"name":"RAG","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Scrum","optional":true},{"name":"Spark","optional":true},{"name":"Time Series","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-07-04T05:52:56Z","employer_posted_date":"2026-07-04","last_verified_at":"2026-10-24T13:16:14Z","board_verified":true,"closed_at":null,"days_open":112,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":111},"description":"Job Summary\nWe are looking for a skilled Machine Learning Engineer to design, develop, and deploy scalable machine learning models and AI-driven solutions. The ideal candidate will have experience in building end-to-end ML pipelines, working with large datasets, deploying models into production, and collaborating with cross-functional teams to solve real-world business problems.\nKey Responsibilities\nDesign, develop, and deploy machine learning models for predictive analytics and intelligent automation.\nBuild and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.\nWork closely with data scientists, software engineers, and business stakeholders to understand requirements and translate them into ML solutions.\nDevelop and optimize supervised, unsupervised, and deep learning models.\nDeploy machine learning models using cloud platforms and MLOps best practices.\nMonitor model performance, retrain models as needed, and ensure production reliability.\nBuild REST APIs or microservices to serve machine learning models.\nPerform data analysis and feature engineering to improve model accuracy.\nDocument technical designs, model performance metrics, and deployment processes.\nStay updated with the latest advancements in Machine Learning, AI, and Generative AI technologies.\nRequired Skills\nStrong programming experience in Python.\nHands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.\nExperience with data manipulation using Pandas, NumPy, and SQL.\nKnowledge of supervised and unsupervised learning algorithms.\nExperience in feature engineering, model evaluation, and hyperparameter tuning.\nFamiliarity with deep learning concepts and neural networks.\nExperience deploying ML models using FastAPI, Flask, or similar frameworks.\nUnderstanding of MLOps concepts, including model versioning, monitoring, and CI/CD.\nExperience with Git and version control.\nStrong analytical, problem-solving, and communication skills.\nPreferred Skills\nExperience with Generative AI, Large Language Models (LLMs), or Retrieval-Augmented Generation (RAG).\nKnowledge of LangChain, LlamaIndex, or similar AI orchestration frameworks.\nExperience with vector databases such as Pinecone, FAISS, Milvus, or ChromaDB.\nFamiliarity with NLP, Computer Vision, or Time Series forecasting.\nExperience with Docker and Kubernetes.\nExposure to Apache Spark or distributed data processing frameworks.\nExperience with MLflow, Kubeflow, or similar MLOps tools.\nCloud & Tools\nPython\nSQL\nScikit-learn\nTensorFlow / PyTorch\nPandas\nNumPy\nFastAPI / Flask\nGit\nDocker\nKubernetes\nMLflow\nAzure ML / AWS SageMaker / Google Vertex AI\nDatabricks (Preferred)\nQualifications\nBachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.\nRelevant certifications in Machine Learning or Cloud platforms are a plus.\nPreferred Experience\n4-8 years of experience in Machine Learning or AI application development.\nExperience building and deploying production-grade ML models.\nHands-on experience with cloud-based ML services.\nExperience working in Agile/Scrum development environments.\nNice to Have\nExperience with recommendation systems, fraud detection, forecasting, or predictive analytics.\nKnowledge of data engineering concepts and ETL pipelines.\nExperience integrating ML models with enterprise applications through REST APIs.\nContributions to open-source ML projects or published research in AI/ML.\nWhat We Offer\nOpportunity to work on cutting-edge AI and Machine Learning projects.\nCollaborative and innovative work environment.\nCareer growth and learning opportunities.\nCompetitive salary and comprehensive benefits.\nFlexible work arrangements (Remote/Hybrid, based on business 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