Data Engineer — ML Training Data Pipeline

Job Title:Data Engineer - ML Training Data Pipeline Notice period: 0-30 Days Experience : 5+ Years Location: Hyderabad OR Pune We are looking for Data Engineer - ML Training Data Pipeline who can Build and maintain the data pipeline that transforms raw production traces into high-quality training datasets for LLM fine-tuning-ingestion, deduplication, format conversion, quality filtering, and train/test splitting at scale on AWS. What We Expect: Build end-to-end data pipelines: raw trace ingestion → dedup → format conversion → quality gating → training-ready datasets Process large-scale JSONL data on AWS S3 (tens of thousands of traces per batch) Convert between chat-completion formats (e.g., OpenAI → Llama 3.1 tool-calling format) Implement smart deduplication and sampling to balance training distribution Design identity-aware train/test splits that measure true generalization Build data validation gates to detect schema drift and format anomalies Create a continuous pipeline that auto-processes new production traces for retraining Requirements Experience: 6+ years data engineering focused on ML data pipelines Python: Strong — pandas, pyarrow, JSONL processing at scale ML Data Libraries: HuggingFace Datasets, Arrow-based storage Data Formats: Multi-turn conversation/chat data structures and tokenizer-specific formatting Deduplication: Content hashing, identity-based grouping strategies AWS: S3, EC2, batch processing workflows Preferred (Not Required): LLM training data prep (chat templates, tool-calling schemas); Axolotl or similar dataset formats; data versioning (DVC, LakeFS); browser-automation trace data or Playwright. Benefits Comprehensive Medical Coverage: Health insurance of INR 5.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind. Robust Protection Plans: Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones. Retirement Benefits: PF and Gratuity provided as per standard government regulations. Flexible Work Options: Enjoy hybrid work arrangements & flexible working hours. Generous Leave Policy: 21 days of annual leave, in addition to 10 company-declared holidays. Employee Well-being Spaces: Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.