Steampunk is looking for a seasoned AI Tech Lead to develop enterprise-grade predictive and generative AI solutions, applications, pipelines, and visualizations for their clients.
Requirements
- Strong programming skills in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Extensive knowledge of machine learning algorithms, deep learning architectures, and natural language processing techniques.
- Proficiency in cloud platforms (AWS, Azure, or GCP) and experience with deploying AI solutions at scale.
- Solid understanding of DevSecOps principles and experience implementing CI/CD pipelines for AI projects.
- Familiarity with big data technologies such as Hadoop, Spark, and distributed computing concepts.
- Experience with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).
- Strong understanding of data structures, algorithms, and software design patterns.
Responsibilities
- Lead and mentor a team of developers working on cutting-edge predictive and generative AI solutions.
- Architect and oversee the development of scalable AI/ML systems, ensuring best practices in software engineering and AI ethics.
- Design and implement end-to-end machine learning pipelines, from data ingestion to model deployment and monitoring.
- Establish and enforce best practices for AI development, including version control, testing, and documentation.
- Oversee the integration of AI models into production environments, ensuring seamless deployment and optimal performance.
- Collaborate with data scientists to translate complex algorithms into efficient, production-ready code.
- Implement and maintain robust MLOps practices to streamline the AI development lifecycle.
Other
- Ability to hold a position of public trust with the US government.
- 5+ years of experience in software engineering, focused on AI/ML development.
- Proven track record of leading and mentoring teams of developers in AI projects.
- Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Demonstrated ability to balance technical leadership with hands-on development when needed.
