Machine Learning Engineer - AI Research
First seen by Alion on Oct 6, 2026.
Role : Machine Learning Engineer - AI Research
Location : Bangalore
Employment Type : Full-time
Experience : 3+ Years
About the Role :
We are looking for a Machine Learning Engineer - AI Research with strong hands-on experience in deep learning, large language models, and model development. The role involves building, fine-tuning, evaluating, and improving AI models for complex, high-accuracy applications.
You will work closely with product, engineering, and domain experts to solve ambiguous AI problems and take solutions from research and experimentation to production.
Key Responsibilities :
- Model Training & Fine-Tuning : Train and fine-tune deep learning and LLM models using domain-specific datasets.
- Model Evaluation : Design benchmarks, evaluation frameworks, metrics, and error-analysis processes to measure model quality and reliability.
- Reinforcement Learning : Develop and implement RL/RLHF and preference-optimization approaches such as PPO, DPO, or similar techniques.
- Research & Experimentation : Conduct structured experiments across models, datasets, architectures, and training approaches while maintaining reproducible experiment records.
- Problem Solving : Independently identify, scope, and solve open-ended ML problems while balancing accuracy, latency, and infrastructure costs.
- Productionization : Translate successful research experiments into reliable, production-ready ML systems.
- Cross-Functional Collaboration : Work with product, engineering, and domain experts to convert real-world requirements into effective AI solutions.
What We're Looking For :
- 3+ years of hands-on experience building, training, and deploying deep learning models in research or production environments.
- Strong experience with deep learning and LLMs, including model training and fine-tuning.
- Practical experience with data curation, model training infrastructure, and large-scale experimentation.
- Experience designing and implementing ML evaluation and benchmarking frameworks.
- Working knowledge of RL, RLHF, PPO, DPO, or preference optimization techniques.
- Strong software engineering and problem-solving fundamentals.
- Experience with experiment tracking tools such as Weights & Biases (W&B), MLflow, or similar platforms.
- Ability to independently work on technically ambiguous problems and take ownership from idea to implementation.
- Strong analytical and communication skills.
Preferred :
- Experience with NLP, Legal AI, document intelligence, or LLM applications.
- Exposure to AI applications in regulated or high-stakes domains.
- Experience taking ML research prototypes into production environments.
What You'll Get :
- Opportunity to work on AI-first products involving LLMs and advanced machine learning.
- High ownership and the opportunity to work on challenging, open-ended ML problems.
- Direct collaboration with experienced product, engineering, and domain teams.
- Opportunity to contribute across the full lifecycle - from research and experimentation to production deployment.
- Competitive compensation based on experience and expertise.
Skills
Machine Learning, AI Integration, IT Research, Deep Learning, LLM, Analytics, NLP, Artificial Intelligence