{"id":1230424,"url":"https://alion.io/job/p99soft-aiml-engineer","title":"AI/ML Engineer","company":{"id":3801201,"name":"P99soft","domain":"p99soft.com","url":"https://alion.io/company/p99soft","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":"middle","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":20000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Prophet","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"MLFlow","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-09-18T11:52:34Z","employer_posted_date":null,"last_verified_at":"2026-09-18T11:52:34Z","board_verified":false,"closed_at":null,"days_open":11,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":11},"description":"Job Description :\n\nWe are looking for a skilled AI/ML Engineer with 4+ years of hands-on experience in developing, evaluating, deploying, and monitoring machine learning solutions.\n\nThe ideal candidate should have strong expertise in Python, machine learning frameworks, time-series forecasting, feature engineering, data preparation, and model optimization.\n\nThe candidate will be responsible for taking ML models from development through production while ensuring performance, reliability, and scalability.\n\nExperience with MLOps, CI/CD, cloud platforms, Generative AI, LLMs, RAG, or Agentic AI will be an added advantage.\n\nKey Responsibilities :\n\n- Design, develop, train, evaluate, and deploy machine learning models for real-world business use cases.\n\n- Develop end-to-end ML pipelines, covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring.\n\n- Perform data preprocessing, cleaning, transformation, feature engineering, and exploratory data analysis.\n\n- Develop and optimize ML models using Python and frameworks such as Scikit-learn, PyTorch, and TensorFlow.\n\n- Develop Time Series Forecasting models using techniques and frameworks such as Prophet and other forecasting approaches.\n\n- Evaluate model performance using appropriate metrics and validation techniques.\n\n- Perform model optimization and hyperparameter tuning to improve accuracy, performance, and scalability.\n\n- Work with structured and unstructured datasets to identify patterns, trends, and insights.\n\n- Build reusable Python-based ML components, pipelines, and applications.\n\n- Deploy ML models into production environments and ensure their reliability and scalability.\n\n- Implement ML model monitoring to track model performance, data quality, drift, and production issues.\n\n- Collaborate with Data Scientists, Data Engineers, Software Engineers, and Product teams to translate business requirements into ML solutions.\n\n- Troubleshoot model and pipeline issues and continuously improve production ML workflows.\n\n- Follow software engineering best practices including version control, testing, documentation, and code reviews.\n\nRequired Skills :\n\n- 4 - 10 years of professional experience in AI/ML, Machine Learning Engineering, Data Science, or a related field.\n\n- Strong programming experience in Python.\n\n- Strong understanding of Machine Learning concepts and algorithms.\n\n- Hands-on experience with machine learning frameworks/libraries such as Scikit-learn, PyTorch, and TensorFlow.\n\n- Experience in Time Series Forecasting, preferably using Prophet or similar forecasting frameworks.\n\n- Strong knowledge of feature engineering and data preparation techniques.\n\n- Experience with model development, training, evaluation, deployment, and monitoring.\n\n- Experience with model optimization and hyperparameter tuning.\n\n- Good understanding of statistics, probability, and data analysis.\n\n- Experience working with Pandas and NumPy.\n\n- Good knowledge of SQL and working with structured data/databases.\n\n- Strong analytical and problem-solving skills.\n\nGood to Have:\n\nMLOps & Production Engineering:\n\n- Knowledge of MLOps practices and machine learning lifecycle management.\n\n- Experience with CI/CD pipelines for ML applications.\n\n- Experience with model versioning and experiment tracking.\n\n- Experience deploying and managing ML models in production environments.\n\n- Familiarity with tools such as MLflow or similar MLOps platforms.\n\n- Experience with Docker/Kubernetes is an added advantage.\n\nCloud & Modern Data Platforms:\n\n- Experience working with cloud platforms such as AWS, Azure, or GCP.\n\n- Exposure to modern cloud-based data platforms and data environments.\n\n- Experience with cloud-based ML services or deployment environments is an advantage.\n\nGenerative AI & Emerging Technologies:\n\n- Experience with Generative AI and Large Language Models (LLMs).\n\n- Knowledge of RAG (Retrieval-Augmented Generation) architectures.\n\n- Experience with embeddings and vector databases.\n\n- Understanding of prompt engineering.\n\n- Exposure to Agentic AI / AI Agents and agent-based architectures.\n\n- Experience integrating LLMs into production applications is an added advantage.\n\nQualifications:\n\n- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, Statistics, or a related field.\n\n- Strong communication and collaboration skills.\n\n- Ability to work independently and as part of a cross-functional team.\n\n- Strong interest in learning and working with emerging AI/ML technologies.\n\nWhat We Offer:\n\n- Opportunity to work on AI/ML and emerging technology initiatives.\n\n- Exposure to real-world Machine Learning, Time Series Forecasting, and AI use cases.\n\n- Opportunity to work with modern cloud, MLOps, and data technologies.\n\n- Exposure to Generative AI, LLMs, RAG, and Agentic AI initiatives.\n\n- Collaborative and learning-focused work environment.\n\n- Career growth opportunities and exposure to innovative projects.\n\nSkills\nArtificial Intelligence, Machine Learning, Generative AI, LLM, Python, Algorithm, PyTorch, Tensorflow","description_format":"text","description_chars":5131,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Growth opportunities"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-25T14:00:00Z"}],"liveness":{"score":68,"band":"ok","label":"Likely open","p_open":1,"p_active":0.756,"p_room":0.9,"age_days":11,"expected_fill_days":17,"reasons":["seen:11","velocity","win:mid"],"computed_at":"2026-09-30T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/p99soft-aiml-engineer","json_url":"https://alion.io/job/p99soft-aiml-engineer.json","meta":{"generated_at":"2026-09-30T06:40:03Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4700,"day_limit":5000,"remaining_today":300,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}