Machine Learning Engineer

Role : ML Engineer

Location : Dallas, TX

Responsibilities:

• Lead a motivated team of AI and ML Engineers and ML Ops Engineers who focus on large scale deployment and integration AI and ML products within time, latency and budget constraints
• Collaborate with our customer, engineering, infrastructure and data science teams to translate their needs or challenges into production-grade Artificial Intelligence and Machine Learning deployment architectures for batch, real-time streaming and edge deployments
• Oversee and guide the development and integration of AI products through common libraries, robust data and CI/CD pipelines, deployment standards and documentation
• Design and implement architecture for an end-to-end machine learning and data discovery platform tailored for RTS customers
• Define the architecture, performance, and power characteristics of high-performance computing systems.
• Develop and optimize software to explore a large design space.
• Analyze various trade-offs within a design space, considering different architectural choices and workloads.
• Collaborate with hardware and software engineers to ensure that the systems meet the requirements of our users.
• Conduct research and development in emerging technologies and trends in high-performance computing.
• Provide technical leadership and mentorship to hardware and software engineers.
• Communicate effectively with stakeholders, including users, partners, and management, to ensure that the systems are delivered on time and within budget.
• Complete other responsibilities as assigned.

Qualifications:

• BS in Computer/Electrical Engineering or Computer Science with 10+ years of working experiences in silicon development, or MS in Computer/Electrical Engineering or Computer Science with 8+ years of relevant working experience, or PhD and 5+ years of relevant working experience preferred.
• Strong background in computer architecture.
• Experiences in developing and optimizing software for high-performance computing systems.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills.
• Ability to work independently and as part of a team.
• Inclusive, adapting your style to the situation and diverse global norms of our people.
• An avid learner, approaching challenges with curiosity and resilience, seeking data to help build understanding.
• Collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, proactively exploring new ideas and adapting quickly to change.
• Experience building Artificial Intelligence and Machine Learning models including efficient deployment architectures based on industry best-practices with ability to make contributions to and peer review of RTS internal Machine Learning libraries and products
• Able to write production-grade code and be familiar with software engineering best practices, including testing, version control and Continuous Integration/Continuous Deployment (CI/CD) frameworks by working closely with internal DevOps teams
• Ability to communicate their findings to both technical and non-technical audience
• Ability to successfully complete technical interviews in areas of deployment frameworks, Artificial Intelligence, statistics, Machine Learning, SQL, Python, PySpark, optimization and Machine Learning Operations