Who we’re looking for…
Role: Sr AI Engineer [MLOps]
Team: AI
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
This Senior AI Engineer [MLOps] role focuses on developing and deploying generative AI models to streamline market research automation, working closely with product managers, designers, and engineers. By leveraging cutting-edge LLM techniques, this position ensures that Knit’s platform can rapidly produce high-quality consumer insights at scale, boosting efficiency and competitive advantage.
Responsibilities | What you will own…
Key performance indicators for this team & role:
Key Performance Indicators (KPIs):
- Model Quality | High-fidelity outputs with robust performance, improved accuracy, and relevance in both ML and LLM pipelines.
- Data Infrastructure | Seamless data ingestion, transformation, and accessibility, ensuring scalability and efficiency.
- Operational Excellence | Streamlined deployment pipelines, reduced downtime, and efficient resource utilization.
Primary responsibilities of this role:
- Design & Optimize ML, LLM, and Data Engineering Solutions | Architect end-to-end pipelines, fine-tune models, and integrate data workflows for actionable insights and trustworthy outputs.
- MLOps & Automation | Develop scalable CI/CD pipelines for model deployment, monitoring, and version control. Ensure reproducibility and operational reliability across environments.
- Data Engineering | Design robust ETL pipelines, manage data lakes/warehouses, and ensure high-quality, secure data for training and inference.
- Validation & Compliance | Conduct pilot tests, ensure adherence to regulatory standards, and mitigate bias in models and data workflows.
- Continuous Improvement | Monitor system performance, optimize pipelines, and contribute to transitioning AI capabilities from niche use cases to mainstream adoption.
Required Skills & Experiences
- LLM & ML Expertise | Proven experience in designing, fine-tuning, and deploying advanced models for 3+ years.
- MLOps Mastery | Strong proficiency in model deployment, orchestration tools (e.g., Kubeflow, MLflow), and CI/CD best practices.
- Data Engineering Skills | Hands-on experience in building and optimizing data pipelines, working with tools like Apache Spark, Kafka, or Airflow.
- Cloud Proficiency | Expertise in cloud platforms (AWS, GCP, Azure) and containerized deployments (Docker, Kubernetes).
- Communication & Analysis | Strong ability to explain technical concepts, align AI initiatives with business goals, and collaborate across teams.
- Adaptability | Eagerness to stay ahead of trends in AI, MLOps, and data engineering, continuously refining skills and approaches.
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.
- We deliver delightful experiences.
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Last updated on Jan 7, 2025