Associate ML Scientist – LLM

This is a fully remote position, open to applicants in India.

📋 Description

• Develop machine learning solutions aimed at addressing significant societal challenges under the mentorship of experienced ML scientists.

• Engage in comprehending stakeholder needs, defining problems, developing models, evaluating, and deploying AI solutions, with a specific emphasis on LLMs and foundational models.

• Utilize machine learning and LLM technologies for social impact by grasping user difficulties and contexts, curating and transforming datasets, adapting and assessing models, creating meaningful evaluation benchmarks, conducting experiments, and extracting insights from data.

• Assist in constructing dependable, scalable AI systems and collaborate closely with engineers, solution providers, domain specialists, and designers to guarantee that solutions are technically robust and practically applicable.

• Collaborate with social sector organizations and stakeholders to grasp real-world requirements and facilitate the successful implementation of AI solutions.

• Keep abreast of developments in LLMs and foundational models, investigate new methodologies as needed, and contribute to the ongoing enhancement of the team's technical skills.

⛳️ Requirements

• A strong enthusiasm for leveraging AI and machine learning to tackle significant societal issues.

• A Bachelor's or Master's degree (or equivalent) in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics, or another quantitative field, accompanied by 1–4 years of relevant work or research experience.

• At least 2 years of hands-on experience in developing and applying machine learning models in either an industrial or research context.

• Proven experience with Large Language Models (LLMs) or foundational models through industry projects, academic research, or substantial open-source contributions.

• A solid grasp of deep learning principles, including Transformer architectures, attention mechanisms, and contemporary representation learning techniques.

• Experience with one or more LLM adaptation methods such as supervised fine-tuning, parameter-efficient fine-tuning (e.g., LoRA/QLoRA), instruction tuning, preference optimization, retrieval-augmented systems, structured generation, or tool-using agents.

• Experience should encompass more than just prompt engineering.

• Proficiency in designing and implementing evaluation strategies for LLM systems, including benchmarking, model analysis, and iterative experimentation.

• Strong software engineering capabilities in Python and familiarity with modern ML frameworks such as PyTorch, Hugging Face Transformers, or equivalent.

• Experience in constructing end-to-end ML systems, which includes data preparation, experimentation, model training, evaluation, and deployment.

• A proven record of applied machine learning projects that address real-world challenges.

• Experience in utilizing LLMs for practical applications is highly advantageous.

• Experience in developing and assessing conversational or multi-turn AI systems is a bonus.

• Exceptional written and verbal communication skills, along with the ability to work efficiently in cross-functional teams.

🏝️ Benefits

• Insurance Benefits - Medical Insurance, OPD Coverage, Accidental Insurance, Life Insurance.

• Wellness Program - Employee Assistance Program, Annual Health Check-Ups, Onsite Medical Centers, Emergency Support System.

• Parental Support - Maternity Benefit, Travel Reimbursement for Expectant Mothers during Last Trimester, Paternity Benefit, Day Care Support Program.

• Mobility Benefits - Travel Policy, Relocation and Deputation benefits, Statutory Benefits - Employee PF Contribution, Gratuity, Leave Encashment.

• Other Benefits – Unlimited Leave Policy, Professional Development Policy, Referral Bonuses, Internet and Telephone Allowance.