MDP - Software Engineer III -Python AI/ML

Overview

Senior Python and Machine Learning Engineer on FactSet's Data domain team, building GenAI, large language model and data engineering solutions for financial data at scale.

What you'll do

• Design, develop, and deploy sophisticated machine learning and GenAI models to solve complex data problems at scale.
• Implement, optimize, and scale ML solutions using Databricks, Spark, and cloud-native data ecosystems (AWS/Azure/GCP).
• Collaborate with other engineers, product managers, and UX teams to build robust, high-performance Python-based analytics pipelines.
• Develop and finetune LLMs and generative AI applications for structured and unstructured financial data.
• Architect data processing workflows leveraging Delta Lake, Feature Stores, and MLOps best practices.
• Translate cutting-edge research (papers, new ML techniques) into production solutions.
• Mentor junior data scientists and engineers on ML, best practices and GenAI.
• Work on one-of-a-kind data challenges, including entity disambiguation, real-time risk analytics, NLP, graph data modeling, and anomaly detection.
• Keep up-to-date with the latest in ML tooling, GenAI, Databricks, and cloud data infrastructure.

What you'll need

• Bachelor's degree in Engineering, Computer Science, or equivalent.
• 3-5 years professional experience in ML, Python programming, and data engineering.
• Deep expertise in Python (NumPy, Pandas, PySpark, FastAPI, etc.) and ML frameworks (TensorFlow, PyTorch, Transformers).
• Practical experience with GenAI: training/fine-tuning LLMs (OpenAI, HuggingFace, Google Gemini, etc.), prompt engineering, and retrieval-augmented generation (RAG).
• Hands-on experience with Databricks (Workspace, MLflow, Delta Lake, Notebooks).
• Strong knowledge of cloud data platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Applied experience with ETL/ELT, data lakes, real-time streaming (Kafka, Spark Streaming).
• Proven track record of tackling cutting-edge data problems at scale.
• Effective communicator with excellent collaboration skills.

Nice to have

• Published research or open source contributions.
• Familiarity with modern MLOps toolchains (MLflow, Airflow, Feature Store, CI/CD).

Details

• Location: Hyderabad, India.