MLOps Engineer - Machine Learning Platform - Toronto

Goldman Sachs Bank AG; Toronto; On-site; CAD 90,000 - 130,000; Full time

Job summary

Goldman Sachs is seeking an MLOps Engineer for its Machine Learning Services team in Toronto. The role involves building and optimizing scalable AI/ML model deployments, developing expertise on AI technologies, and collaborating to provide innovative solutions that drive impactful business outcomes. A competitive range of benefits and support programs enhances the working experience for employees.

Benefits

Health and Medical Insurance

Competitive vacation policies

Retirement planning assistance

Employee medical advocacy services

On-site fitness centers

Child care services

Qualifications

• 2+ years of software development experience using Python.
• Experience with Docker and Unix-based systems.
• Desire to stay updated with AI/ML advancements.

Responsibilities

• Deliver scalable and secure processes for ML model deployment.
• Provide business customers access to cutting-edge AI/ML infrastructure.
• Maintain high quality documentation for engineering and business teams.

Skills

Problem-solving

Collaboration

Technical communication

Education

Bachelor's degree in relevant field

Tools

Python

Docker

Unix-based systems

AWS/GCP

PyTorch

TensorFlow

Terraform

Kubernetes

Job description

MLOps Engineer - Machine Learning Platform - Toronto location_on Toronto, Ontario, Canada

At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Engineering, which is comprised of our Technology Division and global strategists’ groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.

Who We Look For

We are seeking a skilled and motivated engineer to join our Artificial Intelligence Platforms organization as an MLOps Engineer on our Machine Learning Services team. In this role, you will be part of an expert team responsible for our firmwide model registry and real-time serving products in the cloud. A key focus of this position will be on the implementation and optimization of Large Language Models (LLMs) which are pivotal in achieving our Generative AI agenda.

Key Responsibilities:

Deliver scalable, efficient, secure and automated processes for building, deploying and monitoring Machine Learning models

Enable solutions that provide business customers with the ability to leverage the latest and greatest AI/ML infrastructure, frameworks, and tooling to deliver high impact outcomes

Develop and demonstrate deep subject matter expertise on how to optimize machine learning model deployments to scale to the specific needs of each business customer

Author and maintain high quality documentation for both the engineering team as well as for business customers

Remain up to date with the latest advancements in AI/ML frameworks and related technologies

Basic Qualifications:

2+ years of experience in building production software using Python

1+ years of experience as an ML Ops Engineer supporting the production implementation of models

1+ years of experience working with containers (e.g. Docker)

1+ years of experience with Unix-based systems

1+ years of experience delivering solutions in a public cloud (e.g. AWS, GCP)

Strong desire to keep learning and stay up to date with the latest and greatest developments in the model inference domain, especially for Large Language Models (LLMs)

Strong problem-solving skills and the ability to work effectively in a fast-paced and collaborative environment

Preferred Qualifications:

Strong understanding of the end-to-end Model Development Lifecycle (MDLC)

Strong understanding of Python frameworks, packages and tools

Experience building Machine Learning models with frameworks such as PyTorch and TensorFlow

Experience building containerized runtime environments for model serving (e.g. vLLM, SGLang, TensorRT, Triton, AWS Multi Model Server)

Experience with infrastructure-as-code tools, such as Terraform or CloudFormation

Experience with Kubernetes and other container orchestration platforms in the public cloud (e.g. AWS, GCP)

Excellent communication skills and the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

Healthcare & Medical Insurance

We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.

We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.

Financial Wellness & Retirement

We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees’ priorities.

Health Services

We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices.

Fitness

To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount).

Child Care & Family Care

We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.

Benefits at Goldman Sachs

Read more about the full suite of class-leading benefits our firm has to offer.