INTL India - Machine Learning Engineer

Job Description Insight Global is seeking a remote senior INTL (India) Machine Learning Engineer to join a Fortune 10 retail pharmacy client. This person will be joining the team responsible for supporting the organizations retail shopping applications. This AI/ML team will be using customer data to increase sales and elevate customer pain points during their shopping/check out experience.

Compensation:

$12/hr to $16/hr Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401K retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

• 6+ years of Strong experience in Machine Learning & Deep Learning (model design, training, fine-tuning, deployment)
• Hands-on expertise with LLMs, LangChain, embeddings, RAG pipelines, and vector databases
• Proficiency in Python (PyTorch, TensorFlow, Hugging Face, Scikit-learn) and API integration with microservices (Spring Boot / FastAPI / Flask)
• Experience deploying ML/AI models to cloud platforms (GCP preferred
• Vertex AI, BigQuery, Cloud Run, Pub/Sub) with MLOps pipelines (MLflow, Kubeflow, Airflow, GitHub Actions)
• Strong background in data pipelines, feature engineering, large-scale datasets, and SQL/NoSQL databases
• Knowledge of LLM optimization techniques (fine-tuning, quantization, distillation) and multi-modal AI (text, vision)
• Recent GenAI experience
• Familiarity with containerization & orchestration (Docker, Kubernetes/GKE) for scalable deployments
• knowledge of GCP
• Java/microservices experience