We are looking for an accomplished and visionary Lead Software Engineer - Machine Learning to drive the design, development, and deployment of advanced machine learning solutions. This role requires strong leadership, deep technical expertise, and a proven ability to guide teams in solving complex, large-scale problems using cutting-edge ML technologies. As a leader, you will mentor teams, define technical roadmaps, and collaborate across departments to align machine learning initiatives with business objectives.

Responsibilities

• Define and lead the strategy and roadmap for ML systems and applications.
• Architect and oversee the development of scalable machine learning systems and infrastructure.
• Drive the design and implementation of advanced ML models and algorithms to address complex business problems.
• Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to identify ML use cases and requirements.
• Mentor and guide junior and mid-level engineers in best practices for ML development and deployment.
• Monitor, evaluate, and improve the performance of machine learning systems in production.
• Ensure compliance with industry standards and best practices for model development, data governance, and MLOps.
• Lead research initiatives to explore emerging ML techniques and integrate them into the organization's solutions.

Required Skills/Qualifications

Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. A Ph.D. is a plus.

Technical Skills:

• 10+ years of experience in software engineering, with at least 5 years focusing on machine learning.
• Proficiency in ML frameworks and libraries like TensorFlow, PyTorch, and scikit-learn.
• Strong expertise in designing and building large-scale, distributed ML systems.
• Advanced knowledge of data engineering tools and frameworks, such as Spark, Hadoop, or Kafka.
• Hands-on experience with cloud platforms (AWS, GCP, Azure) for ML workloads.
• Expertise in deploying and managing ML models in production environments using MLOps tools like MLflow or Kubeflow.
• Deep understanding of algorithms, data structures, and system design.
• Experience with containerization (Docker) and orchestration (Kubernetes).

Experience: 10+ years of experience in data engineering or related fields.

Soft Skills:

• Strong leadership and decision-making capabilities.
• Exceptional problem-solving and analytical thinking.
• Excellent communication skills to convey technical concepts to both technical and non-technical audiences.
• Ability to foster collaboration and drive innovation across teams.

Preferred Skills/Qualifications

Education: Master’s degree in Computer Science, Information Technology, or related field.

Technical Skills:

• Familiarity with cutting-edge techniques like generative AI, reinforcement learning, or federated learning.
• Experience in building and managing real-time data processing pipelines.
• Knowledge of data security and privacy best practices, particularly in regulated industries.
• Publications or patents in the field of machine learning or artificial intelligence.

Experience: 10+ years

Key Performance Indicators:

• Successful delivery of scalable, high-impact ML solutions aligned with business goals.

• Effective mentorship and upskilling of team members.

• Continuous improvement of ML system performance and reliability.

• Innovation and adoption of emerging ML techniques to maintain a competitive edge.