Technical Lead (AI/ML)

Job Overview

We are looking for a motivated and experienced Tech Lead – AI/ML to join our team and drive the development of cutting-edge AI/ML solutions. This role combines hands-on technical expertise with leadership responsibilities, guiding a team to build scalable, efficient, and impactful AI/ML models. The ideal candidate should have a strong foundation in machine learning, data science, Generative AI, RAG approaches, and has deep understanding how data projects work coupled with experience leading teams or projects.

Key Responsibilities

Technical Leadership:

• – Provide technical guidance and mentorship to a team of AI/ML engineers.
• – Lead project planning, design reviews, and architecture discussions.
  
  

AI/ML Model Development

• – Design, develop, and optimize machine learning and deep learning models to meet business objectives.
• – Perform feature engineering, hyperparameter tuning, and validation of models.
  
  

Generative AI And Advanced Solutions

• – Implement and enhance Generative AI models such as LLMs or GANs.
• – Identify opportunities for using Generative AI to innovate and improve solutions.
  
  

MLOps And Deployment

• – Deploy AI/ML models into production with robust CI/CD pipelines.
• – Monitor and maintain deployed models, ensuring performance and scalability.
  
  

Collaboration

• – Work closely with product managers, data engineers, and other stakeholders to define requirements and deliverables.
• – Act as the technical liaison for internal and external partners.
  
  

Innovation And R&D

• – Stay up to date with advancements in AI/ML technologies and incorporate best practices into projects.
• – Explore new tools, libraries, and frameworks to enhance team capabilities.
  
  

Technical Expertise

Required Skills and Qualifications

• – Strong knowledge of machine learning frameworks like TensorFlow or PyTorch.
• – Proficiency in Python and ML libraries (e.g., Scikit-learn, Pandas, NumPy).
• – Experience with NLP (e.g., BERT, GPT) or computer vision models (e.g., YOLO, OpenCV).
  
  

Generative AI Knowledge

• – Hands-on experience with Generative AI technologies and real-world applications.
  
  

Data Engineering And Analysis

• – Proficiency in SQL and working knowledge of big data tools like Apache Spark.
• – Experience building data pipelines and ensuring data quality.
  
  

Deployment And Cloud Platforms

• – Familiarity with Docker, Kubernetes, and MLOps tools like MLflow.
• – Experience with cloud platforms such as AWS, Azure, or GCP.
  
  

Soft Skills

• – Strong communication and collaboration skills.
• – Proven ability to mentor junior engineers and lead technical teams.
  
  

Preferred Skills

• – Exposure to reinforcement learning or federated learning.
• – Experience optimizing models for edge devices or IoT.
• – Knowledge of monitoring production models for drift and retraining.