Associate ML Scientist (LLM) - II

Wadhwani AI; United States; On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Medical Insurance

Wellness Program

Parental Support

Mobility Benefits

Statutory Benefits

Other Benefits

Job summary

Wadhwani AI is seeking an Associate Machine Learning Scientist to tackle societal challenges using ML and LLMs. You will develop, adapt, and evaluate modern ML systems beyond basic prompt engineering, collaborating with cross‑functional teams to translate real‑world problems into deployable AI solutions.

You will stay current with advances in LLMs, design robust evaluation benchmarks, conduct experiments, and contribute to scalable AI systems in a remote setting.

Qualifications

• Bachelor's or Master's degree in a quantitative field.
• 1–4 years of relevant work or research experience.
• Hands‑on ML experience with models and ML systems.

Responsibilities

• Build ML solutions addressing societal challenges with senior guidance.
• Work on data curation, model development, evaluation, and deployment of AI solutions focused on LLMs.
• Collaborate with engineers, domain experts, and designers to ensure practical utility of AI solutions.

Skills

Machine Learning

Python

Cross-functional collaboration

Transformer models

LLMs

Experimentation

Education

Bachelor's or Master's degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics, or related field

Tools

PyTorch

Hugging Face Transformers

LoRA/QLoRA

data processing

Job description

This is a remote position. We are looking for an Associate Machine Learning Scientist with a strong foundation in machine learning and hands‑on experience working with Large Language Models (LLMs) and related technologies. The ideal candidate is passionate about applying AI to solve high-impact societal challenges and has experience developing, adapting, and evaluating modern ML and LLM‑based systems beyond prompt engineering and basic RAG pipelines. They should enjoy working in cross‑functional teams, translating real‑world problems into deployable AI solutions, and continuously learning from advances in the rapidly evolving LLM ecosystem.

Responsibilities

• As an Associate Machine Learning Scientist, you will build machine learning solutions to problems of societal importance under the guidance of senior ML scientists. You will participate in understanding stakeholder requirements, problem definition, model development, evaluation, and deployment of AI solutions, with a particular focus on LLMs and foundation models.
• To apply machine learning and LLM technologies for social good, you will need to understand user challenges and their context, curate and transform data, adapt and evaluate models, design meaningful evaluation benchmarks, conduct experiments, and derive insights from data. You will contribute to building reliable, scalable AI systems and work closely with engineering, solutions, domain experts, and designers to ensure that solutions are technically sound and practically useful. You will also interact with social sector organisations and stakeholders to understand real‑world needs and help ensure successful deployment of AI solutions.
• You will be encouraged to stay current with advances in LLMs and foundation models, explore new techniques where appropriate, and contribute to the continuous improvement of the team's technical capabilities. Excellence as an individual contributor goes together with strong collaboration, curiosity, and a willingness to both learn from and share knowledge, ideas, and emerging practices with the team.

Requirements

• Passion for applying AI and machine learning to solve large societal challenges.
• Bachelor's or Master's degree (or equivalent) in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics, or another quantitative discipline, with 1–4 years of relevant work or research experience.
• Minimum 2 years of hands‑on experience developing and applying machine learning models in an industry or research setting.
• Demonstrated experience working with Large Language Models (LLMs) or foundation models through industry projects, research, or significant open‑source contributions.
• Strong understanding of deep learning fundamentals, including Transformer architectures, attention mechanisms, and modern representation learning techniques.
• Experience with one or more LLM adaptation techniques 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 extend beyond prompt engineering alone.
• Experience designing and implementing evaluation methodologies for LLM systems, including benchmarking, model analysis, and iterative experimentation.
• Solid software engineering skills in Python and experience with modern ML frameworks such as PyTorch, Hugging Face Transformers, or equivalent.
• Experience building end‑to‑end ML systems, including data preparation, experimentation, model training, evaluation, and deployment.
• Track record of applied machine learning projects addressing real‑world problems. Experience applying LLMs to practical use cases is highly desirable.
• Experience building and evaluating conversational or multi‑turn AI systems is a plus.
• Excellent written and verbal communication skills and the ability to work effectively in cross‑functional teams.

Wadhwani AI - Full Time Employee Benefits (Not applicable for Intern or Contract Roles)

• - 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.

We care deeply about the well‑being of our employees and their families. You will get an opportunity to take on roles beyond a defined job description. These are just some of the reasons why working with us is more than just a job it's a chance to grow, thrive and contribute to society.