Sr. Machine Learning Engineer - GenAI
Location: Remote with occasional travel to Bangalore
ARTPARK at IISc, India’s top research university, harnesses the best in AI and Robotics for impact in the developing world. We build deep-tech startups and innovations, lead national scale data & AI platforms, and create award-winning solutions for societal challenges.
Our international ecosystem spans leading researchers, startups, corporates, governments, and nonprofits. Our partners include Office of PSA (Principal Scientific Advisor to the Government of India), MEITY’s Bhashini, ICMR (Indian Council of Medical Research), AIIMS, NCBS, TIFR, EkStep, Gates Foundation, GIZ, Rockefeller Foundation, Cisco, Google, Nokia, nVidia, ARMMAN, FIND, PATH, states, cities, and many others.
We are seed-funded by the Department of Science & Technology (Government of India) and Government of Karnataka.
Generative AI at Artpark
ARTPARK’s Generative AI team collaborates with high-impact nonprofits to leverage Large Language Models (LLMs) and solve real-world challenges. We are a small, mission-driven team offering a unique opportunity to apply your skills and talent for social good.
In a recent partnership with ARMMAN, funded by the Gates Foundation, we developed and integrated LLM bots into training tools designed to help health workers manage high-risk pregnancies in the field. The project won the Global Grand Challenge on Equitable AI and was featured in Gates Notes as one of “the coolest innovations” Bill Gates encountered.
Learn more about our initiatives
The Role
Join us on our journey to improve millions of lives, using AI.
We are looking for an experienced Machine Learning Engineer to join our team. In this role, you will design, build, and fine-tune our Large Language Models (LLMs), collaborating with the Director of Machine Learning and our engineering team.
At ARTPARK, we don't simply tinker behind closed doors: your work will be shared with the community through publications and open-source contributions, amplifying your voice within the AI community. Working here is more than a job – it is an opportunity to develop breakthrough technologies and make a tangible difference in people’s lives.
Key Responsibilities
1. Lead the development and fine-tuning of LLMs
2. Design scientifically rigorous experiments and implement machine learning models, run experiments, and iterate to produce high-quality results.
3. Collaborate with cross-functional teams, including software engineers and data scientists, to ensure efficient execution of the machine learning roadmap.
4. Work closely with the Director of Machine Learning to define the technical strategy for the development and scaled deployment of LLMs.
5. Implement testing and analytics for continuous model improvement.
About You
An ideal candidate for the role of Sr. Machine Learning Engineer at ARTPARK will have the following qualifications and experience as minimum requirements:
1. Bachelors or above degree in Computer Science, AI, Machine Learning, or related technical field. Exceptional candidates without formal qualifications with demonstrable project experience are also considered.
2. Demonstrated commitment to excellence and an inclination towards producing high-quality work, drawing from both theoretical understanding and practical consideration
3 Empirical and experimental mindset with a focus on careful consideration of data, model, evaluation and error analysis in order to make iterative, measurable progress in model performance.
4. Experience working with machine learning libraries and frameworks (such as PyTorch, Hugging Face). Familiarity with Natural Language Processing (NLP).
5. Proficiency in Python and a solid understanding of machine learning principles
6. Ability to adapt and learn in a fast-paced environment.
Nice-To-Haves
The following will give you an edge over others:
1. Expertise building large language models (LLMs) and agentic systems.
2. Appreciation of equity and inclusion issues, particularly in relation to UN Sustainable Development Goals (SDGs).
3. Previous experience in projects involving the design, development, and deployment of ML models.
5. Hands-on experience with cloud services like AWS, GCP, or Azure.
6. Knowledge of database technologies (SQL, NoSQL).
7. Publications in top AI/ML conferences