GIST Impact - AI/ML Engineering Lead - R/Python (4-8 yrs)

About :

GIST Impact is a leading impact data, analytics and product solutions provider that has been measuring, quantifying and valuing corporate impacts for more than 16 years. With a team of 100+ scientists, engineers, data scientists and environmental economists, GIST Impact delivers market-leading impact platforms and datasets, covering 14,000+ companies with geographically precise, time-series data. GIST Impact works with pioneering companies across all sectors and with investors representing over $8 trillion in assets under management. GIST Impact also partners with some of the world's largest ESG data providers, business networks, and fintech platforms to enable impact measurement across global markets.

Founded by Pavan Sukhdev (ex-banker, environmental economist, President of WWF International, and winner of the 2020 Tyler Prize for the Environment), GIST Impact is at the cutting edge of measuring impacts using a scientifically sound and economically rigorous methodology that provides unique and unparalleled insight into how companies impact society and the environment. In addition, our leadership team comprises product, technology and commercial leaders who have worked across Meta, Adobe, AT Kearney, Bain & Co., McKinsey & Co., Monitor Deloitte, etc.

Role Description :

We are looking for a highly skilled and motivated AI/ML Engineering Lead with 4-8 years of experience to lead the design, development, and deployment of advanced AI/ML solutions.

- This role requires a balance of technical expertise and leadership skills to solve complex problems, innovate with scalable systems, and deliver impactful AI-driven applications.

- The ideal candidate will have a proven ability to translate business objectives into cutting-edge technical solutions while mentoring a team of engineers and collaborating across departments.

- Experience with Generative AI, Large Language Models (LLMs), and modern AI frameworks is a significant advantage.

Job Duties and Responsibilities :

Leadership and Team Collaboration :

- Lead a team of AI/ML engineers and data scientists, fostering innovation, knowledge-sharing, and a collaborative work environment.

- Translate business goals and challenges into technical solutions, working closely with stakeholders to ensure alignment and impact.

- Provide technical mentorship on the development and deployment of LLMs and Generative AI systems.
Model Development and Optimization

- Design and implement machine learning models and pipelines for diverse applications such as predictive analytics, NLP, computer vision, and recommendation systems.

- Develop and fine-tune LLMs and Generative AI models for specific use cases, ensuring optimal performance and scalability.

- Leverage frameworks such as LangChain, LlamaIndex, and the RAG (Retrieval-Augmented Generation) framework to build context-aware AI solutions.

- Integrate cutting-edge techniques in generative AI, such as text generation, summarization, and conversational agents.

Infrastructure and Deployment :

- Build and maintain scalable infrastructure for AI/ML model development and deployment using MLOps best practices.

- Implement production-grade pipelines for Generative AI and LLMs, ensuring low latency and high availability.

- Leverage cloud platforms (e.g., AWS, Azure, Google Cloud) to ensure efficient resource utilization and cost-effectiveness.

Best Practices and Innovation :

- Establish and enforce best practices for model development, code versioning, and reproducibility.

- Stay updated with the latest advancements in Generative AI, LLMs, and tools like LangChain and LlamaIndex, and integrate them into projects as appropriate.

- Ensure compliance with ethical AI standards and data privacy regulations.

Required Skills and Experience :

Technical Skills :

- Strong programming skills in Python, R, or similar languages.

- Hands-on experience with ML frameworks and libraries like TensorFlow, PyTorch, Scikit-learn, or Keras.

- Expertise in working with Generative AI models and LLMs, such as GPT, BERT, or similar architectures.

- Proficiency in frameworks like LangChain, LlamaIndex, and RAG for context-aware AI applications.

- Practical experience with vector databases and semantic search techniques.

- Proficiency in data engineering, including ETL processes, data cleaning, and feature engineering.

- Experience with cloud computing platforms such as AWS, Azure, or Google Cloud for AI/ML solutions.

- Knowledge of MLOps tools and techniques for automating the AI/ML lifecycle. Experience

- 4-8 years of experience in AI/ML engineering with a proven record of deploying solutions in production environments.

- Demonstrated experience in leading projects and collaborating with cross-functional teams.

- Hands-on experience with deploying Generative AI solutions and LLM-based applications.

- Practical knowledge of handling large datasets and implementing big data technologies like Hadoop or Spark.

Soft Skills :

- Excellent problem-solving and critical thinking abilities.

- Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.

- A growth mindset and passion for innovation in the AI/ML domain.