Artificial Intelligence/Machine Learning Lead

About the Role :

We are seeking an experienced AI/ML Lead to spearhead the design, development, and deployment of cutting-edge artificial intelligence and machine learning solutions. You will work at the intersection of data science, engineering, and product, leading teams to solve complex business problems using advanced AI/ML techniques. The ideal candidate will have a strong technical background, proven leadership skills, and the ability to drive innovation from research to production at scale.

Key Responsibilities :

Strategy & Leadership :

- Lead and mentor a high-performing team of ML engineers, data scientists, and researchers.

- Foster a culture of innovation, collaboration, and continuous learning within the AI/ML team.

- Evaluate emerging AI technologies and tools, recommending adoption where beneficial.

Solution Development :

- Oversee the full ML lifecycle: data collection, preprocessing, feature engineering, model selection, training, evaluation, and deployment.

- Ensure reproducibility, scalability, and maintainability of ML models in production.

- Drive the application of Generative AI, LLMs, Computer Vision, NLP, or other advanced techniques depending on business needs.

Collaboration & Stakeholder Management :

- Communicate complex technical concepts to non-technical stakeholders effectively.

- Collaborate with DevOps/DataOps to ensure reliable, secure, and efficient ML pipelines and deployments.

Governance & Best Practices :

- Ensure compliance with ethical AI practices, data privacy regulations (GDPR, CCPA, etc.), and security standards.

- Define and monitor KPIs for AI/ML initiatives, ensuring measurable business impact.

Qualifications :

Education : Bachelors/Masters/Ph.D. in Computer Science, Data Science, AI/ML, or a related field.

- 5+ years of experience in software/data engineering or AI/ML roles.

- Proven track record of deploying ML models into production at scale.

Technical Skills :

- Experience with Generative AI/LLMs (e.g., GPT, LLaMA, Hugging Face Transformers).

- Solid understanding of NLP, Computer Vision, or Recommendation Systems.

- Strong knowledge of MLOps, CI/CD for ML, and deployment frameworks (e.g., MLflow, Kubeflow, SageMaker).

- Proficiency with big data and cloud platforms (AWS, GCP, Azure).

- Hands-on expertise in SQL/NoSQL databases and distributed data systems (Spark, Hadoop, etc.).