Staff Model Risk Specialist governing machine learning and GenAI applications for Upstart, an AI lending marketplace. Evaluating model risks, controls, monitoring, and regulatory governance for Upstart Bank.
About the role
- Principal ML Engineer at a global networking leader shaping ML strategy and building intelligent systems for network management. Driving innovation in fields like Generative AI and Data Mining.
Responsibilities
- Define and drive the technical vision for ML solutions across products and platforms
- Own the end-to-end software development lifecycle — from design and code reviews through to deployment and operations
- Architect high-performance, scalable microservices, including synchronous and asynchronous web services
- Build real-time inference pipelines for complex models using Triton, TensorRT, and mixed-precision computing
- Mentor engineers, set technical direction, and foster a strong team culture
- Champion engineering excellence, system resilience, and continuous operational improvement
Requirements
- Degree in Computer Science, Mathematics, or a related field
- 5–10 years of full software development lifecycle experience (design, coding, testing, deployment, and operations)
- 5–10 years of Python expertise, including advanced features and libraries
- Strong experience designing RESTful APIs (e.g., FastAPI)
- Proficiency with Docker, Kubernetes, and CI/CD pipelines
- 3+ years designing and architecting large-scale distributed systems on cloud platforms (AWS, Azure, or GCP)
- Proven experience as a tech lead or engineering mentor
- MS or PhD in Computer Science or ML
- Hands-on experience with ML frameworks: PyTorch, SageMaker, Triton, or TensorRT
- Familiarity with NoSQL and document databases
- Track record of handling big data, optimising workflows, and improving system performance
Benefits
- Health Care Plan (Medical, Dental & Vision)
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Public Holidays)
- Family Leave (Maternity, Paternity)
- Training & Development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Student machine learning software engineer building end - to - end AI solutions at RBC Borealis, Royal Bank of Canada’s AI and data innovation group. Collaborating with researchers and business teams on algorithms, distributed data processing, and production - ready software.
Senior Machine Learning Engineer building causal and decision systems for CSC Generation’s consumer businesses. Developing pricing and other commercial automation using experimentation, uncertainty, and policy learning.
Senior Deep Learning Engineer developing player - tracking, evaluation, and forecasting models for SumerSports’ football intelligence platform. Driving research threads into production for NFL and NCAA teams.
LP
Machine_Learning_Specialist / Data Scientist / AI Developer
LinkedIn Recruiter Post
We are seeking a Machine Learning Specialist / Data Scientist / AI Developer with 6+ years of experience in Python, R, SQL, and machine learning.
Machine Learning Specialist developing AI, models, and analytical data products for the Government of Alberta. Applying machine learning to improve public services and policymaking.
Machine Learning Engineer developing production AI models and scalable MLOps platforms for Wave, which helps small businesses thrive. Collaborating on financial - risk applications, governance, observability, and reliable deployment.
Senior Geospatial ML Engineer building satellite - imagery vegetation intelligence for a climate - tech company. Improving production models and pipelines to help utilities prevent wildfires and outages.
Senior Machine Learning Engineer building scalable recommender systems for Thomson Reuters’ legal, tax, compliance, government, and media platforms. Implementing secure ML products and infrastructure.
ML Engineer scaling Torc Robotics’ simulation platform for autonomous trucks. Embedding with Autonomy teams to operationalize replay, recompute, metrics, visualization, and model integrations.