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.
Roles and 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
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.