Machine Learning Engineer
1 week ago
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
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