We are seeking an experienced Machine Learning Manager to lead a team of data scientists, ML engineers, and GenAI experts. In this role, you will be responsible for overseeing the design, development, and deployment of scalable ML/LLM models, driving innovation, and mentoring your team. The ideal candidate will have a strong technical foundation, a proven track record in ML/AI solutions, and the leadership skills to guide a diverse team of professionals to deliver impactful results.

Key Responsibilities:

• Team Leadership: Lead and mentor a team of machine learning and Generative AI engineers, fostering innovation and ensuring the team delivers high-quality solutions.
• End-to-End ML Workflows: Manage the end-to-end lifecycle of machine learning, deep learning, and GenAIworkflows, including data preprocessing, model development, fine-tuning, deployment, and ongoing monitoring.
• Cross-Functional Collaboration: Work closely with product managers, software engineers, and business stakeholders to ensure alignment on goals and project deliverables.
• Research G Experimentation: Lead the team in exploring new methodologies in ML and Generative AI, keeping up-to-date with technological advancements.
• Scalability G Efficiency: Ensure that ML models in production are scalable, efficient, and reliable, optimizing for performance and stability.
• KPIs G Evaluation: Define key performance indicators (KPIs) to track the success of ML initiatives and drive improvements.
• Best Practices Advocacy: Promote best practices in ML engineering, data engineering, and software development across the the team.
• Adoption of New Technologies: Stay current with advancements in AI/ML, pushing for the adoption of cutting-edgetechnologies.
• Project Management: Oversee project timelines, resource allocation, and deliverables, ensuring projects are completed on time and within scope.
• Team Development: Contribute to the recruitment, training, and professional development of the ML/GenAIteam. 
• Generative AI Strategy: Develop a strategic roadmap for Generative AI, ensuring it aligns with business goals and drives innovation within the organization.
• Advocacy for GenAI: Champion the adoption of Generative AI technologies across the organization, unlocking new opportunities for business growth.

Required Skills G Ǫualifications:

• Education: Bachelor’s or Master’s degree in Data Science, Machine Learning, or a related field (PhD is preferred).
• Experience: 10+ years of experience in machine learning or data science, with at least 2+ years in a leadership role.
• Technical Expertise:
  • Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Proficiency in programming languages such as Python and R.
  • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and MLOps tools (e.g., MLflow, Kubeflow).
  • Strong knowledge in data preprocessing, feature engineering, and statistical modeling.
  • Proven success in deploying ML models at scale in production.
  • Excellent communication skills to convey technical information to both technical and non-technical stakeholders.

Preferred Skills G Ǫualifications:

• Familiarity with big data technologies (e.g., Spark, Hadoop).
• Experience managing distributed systems and real-time data pipelines.
• Domain expertise in a specific industry (e.g., healthcare, finance, e-commerce).
• Certifications in AI/ML or cloud technologies.
• Extensive hands-on experience with Generative AI models, including:
  • Large Language Models (LLMs) (e.g., GPT, PaLM, Llama)
  • Text-to-Image/Video Models (e.g., DALL·E, Stable Diffusion)
  • Generative Adversarial Networks (GANs)
  • Reinforcement Learning from Human Feedback (RLHF) 
    
    
• Why Join Us?
  
• Lead high-impact projects in a rapidly evolving field with access to the latest AI/ML tools and technologies.
• Competitive salary and benefits.
• A supportive and inclusive work environment that values growth and professional development.
• Opportunity to work on cutting-edge Generative AI solutions in the healthcare domain, making a significant impact on business outcomes.