Software Engineer delivering MLOps solutions for Generative AI at DataGalaxy. Focusing on reliability and collaboration with product engineering teams in a hybrid environment.
About the role
- Senior Machine Learning Architect at Boeing designing scalable ML systems and architectures. Collaborating with teams to implement data-driven solutions for business challenges.
Responsibilities
- Define the strategy to build highly reliable and scalable ML and AI solutions that align with the organization’s business goals and objectives
- Lead the creation and implementation of scalable, robust, and high-performance ML architectures including MLOps, AIOps leveraging cloud native services (AWS, Azure, GCP) and open-source frameworks
- Design, build, and optimize machine learning models, ensuring accuracy, efficiency, and scalability
- Collaborate with data engineers, data scientists, software developers, and DevOps teams to integrate ML models into production systems
- Assess and recommend ML tools, frameworks, and platforms to deliver business value and foster innovation
- Monitor and optimize ML models and systems for latency, throughput, and cost-efficiency in production
- Provide technical guidance to ML engineers and data scientists including documenting standards and best practices
- Ensure ML systems adhere to ethical guidelines, data privacy regulations, and industry standards
- Design and development of Generative AI and AI use cases (LLMs, RAG, Agentic, multi model AI, fine tuning. Vector databases and prompt engineering)
- Lead organizational change for the adoption of new platforms, machine learning tools and analytics workflows
- Own all communication and collaboration channels pertaining to strategy and assigned projects, including regular stakeholder, senior leadership and cross-team updates
Requirements
- Bachelor’s degree or higher
- 5+ years of experience with AI/ML technologies, frameworks, models and ensembles
- 5+ years of experience with Pytorch, SciKit Learn, Tensorflow, or similar backend frameworks
- 5+ years of experience with Kubernetes, Docker containers, and Ansible
- 5+ years of experience with data engineering and data pipelines for On-Prem cloud, hybrid data models and data warehouses
- 5+ years of experience with DevOps software including Gitlab, Ansible, Terraform, Jira, Azure DevOps Pipelines, GitHub, AWS CodeBuild, AWS CodePipelines, AWS CodeGuru
- 5+ years of experience with software programming/scripting (such as Python, Unix/Linux type batch scripting, FORTRAN, C / C++)
Benefits
- health insurance
- flexible spending accounts
- health savings accounts
- retirement savings plans
- life and disability insurance programs
- paid and unpaid time away from work
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