AI / ML Engineer

We are looking for passionate ML/AI Engineers to join our AI Foundry team and contribute across the following: AI Model Engineering Data Intelligence and Curation Foundation Model Training Scientific Data Systems Distributed AI Infrastructure This role is ideal for engineers who enjoy solving deep AI systems problems and want to work on large-scale foundation models, scientific datasets, and next-generation AI infrastructure.

Responsibilities:

• Support development and optimization of foundation model training workflows.
• Work on transformer architectures, model fine-tuning, and evaluation systems.
• Build and maintain data intelligence and curation pipelines.
• Implement data preprocessing, deduplication, tokenization, and quality scoring workflows.
• Support RLHF/alignment and benchmarking systems.
• Work with scientific and multilingual datasets.
• Collaborate with AI infrastructure and platform engineering teams.
• Contribute towards scalable GPU/TPU-based AI systems.

Requirements:

• Experience: 0-5 years.
• Strong Python programming skills.
• Understanding of machine learning and deep learning fundamentals.
• Hands-on exposure to PyTorch or similar ML frameworks.
• Understanding of transformers, LLMs, or foundation model concepts.
• Familiarity with NLP preprocessing or data pipeline concepts.
• Strong debugging and problem-solving mindset.
• Comfortable working in Linux environments.
• Good to Have: DeepSpeed / FSDP / Distributed Training RLHF / DPO workflows, CUDA, or GPU optimization exposure PySpark / Data Engineering exposure Scientific ML or numerical computing exposure Dataset curation and benchmarking knowledge of HPC / GPU cluster exposure.
• Deeply curious, enjoy solving difficult systems problems, love building from first principles, and are willing to continuously scale up and upskill in AI engineering.
• Candidates with only wrapper/application-layer AI experience may not be the right fit for this role.