Lead AI Engineer
Knit
Who we’re looking for…
Role: Lead AI Engineer
Reports To: Head of AI
Location: India. We are prioritizing candidates in the Delhi area. This role is expected to work in the Indian time zone, IST.
Travel: This role will be expected to make annual travel 3-4 times domestically in India and 1-2 times internationally to the US. Note, Knit US does US All Team, in-person company events twice per year.
A little about us…
Knit is the The Researcher-Driven AI Platform helping researchers run agency-quality quant + qual research at DIY costs & speed. Through Knit, brands like NASCAR, JBL, and Mars automate their consumer research process to get a quicker and more holistic understanding of their audiences.
Overview
The Lead AI Engineer role involves overseeing the development and deployment of advanced AI models, with a focus on LLMs, MLOps, and data engineering, while ensuring alignment with the overarching vision set by the leadership. The Lead AI Engineer collaborates closely with product managers, designers, and cross-functional teams to deliver scalable, high-impact solutions that enhance market research automation and consumer insight generation.
Responsibilities | What you will own…
Key Performance Indicators (KPIs):
- Model Performance | Achieve high accuracy, explainability, and efficiency in deployed AI models, ensuring their real-world applicability.
- Operational Excellence | Implement scalable and reliable systems with minimal downtime, latency, and resource overhead.
- Scalability & Adaptability | Successfully design systems and applications capable of scaling to handle increasing data volumes and diverse user needs.
- User Impact | Drive measurable improvements in user satisfaction and adoption rates of AI-driven features and applications.
Primary responsibilities of this role:
- AI Model Innovation | Lead the creation, fine-tuning, and deployment of LLMs and ML models to extract actionable insights and drive automation.
- MLOps & Data Engineering | Architect and maintain robust CI/CD pipelines, ensure data quality with scalable ETL workflows, and optimize model deployment lifecycles.
- Scalability & Reliability | Ensure all systems, including AI models and applications, can handle growing data and user demands while maintaining performance and stability.
- Cross-Functional Collaboration | Work closely with product managers, designers, and engineering teams to ensure AI solutions are integrated effectively across platforms.
Required Skills & Experiences
- LLM & ML Expertise | Deep experience in developing, fine-tuning, and deploying LLMs and other advanced ML models for 7+ years.
- MLOps Competence | Expertise in CI/CD pipelines, orchestration tools like Kubeflow or MLflow, and model lifecycle management.
- Data Engineering Proficiency | Strong knowledge of designing scalable ETL workflows and managing data pipelines with tools like Spark, Kafka, and Airflow.
- Cloud & Infrastructure Awareness | Hands-on experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes).
- Innovation Approach | A forward-thinking mindset to identify trends in AI, MLOps, and full-stack development, ensuring the team stays ahead of the curve.
Benefits
Upon joining the Knit team, you will receive a competitive salary + Equity Options if applicable to role, Healthcare Coverage, a company-issued laptop, contributions to the Employee Provident Fund (EPF), holiday time-off, and more!
Our Company Values
- We are thoughtful of others.
- We are mindful of ourselves.