MLOps Engineer

United Software Group Inc. - Canada; Canada; On-site; CAD 80,000 - 100,000; Full time

Job summary

An innovative company is seeking an MLOps Engineer to enhance model deployment and performance monitoring. In this role, you will focus on optimizing training and inference costs, implementing continuous integration and delivery pipelines, and collaborating with machine learning engineers and data scientists. Your expertise in programming languages such as Python, Scala, and Java, along with hands-on experience in tools like Databricks and mlFlow, will be crucial. This position offers the opportunity to work in a dynamic environment, driving the operationalization of machine learning models and ensuring best practices are followed. If you're passionate about MLOps and eager to make an impact, this is the perfect role for you.

Qualifications

• 3 years of MLOps experience with strong programming skills.
• Advanced degree in Computer Science focusing on software/platform engineering.

Responsibilities

• Deploy and monitor ML models, optimizing performance and costs.
• Collaborate with cross-functional teams to implement best practices.

Skills

Python

Scala

Java

Problem-solving skills

Analytical skills

AWS ecosystem

Education

Master’s degree in Computer Science

Tools

Databricks

mlFlow

Seldon

Git

Docker

Kubernetes

Jenkins

Prometheus

Grafana

Snowflake

Kubeflow

Tecton

Prow

Bazel

ArgoCD

Job description

Job Posting Title

MLOps Engineer

Position Overview:

You Will:

1. Focus on model deployments & performance monitoring, training & inference cost optimizations, tech stack upgrades & migrations.
2. Design, improve, and implement best practices in continuous integration and delivery pipelines to speed the rate at which our machine learning engineers can go from ideation to operationalizing machine learning models in a repeatable manner.
3. Setup new model training pipelines ensuring proper tagging, monitoring, alerting, and logging are in place.
4. Deploy projects into a streamlined environment strategy ensuring they can take advantage of best practices.
5. Identify cost savings in areas where computation and storage utilized for model training and inference can be optimized.
6. Support existing day to day requests through our service desk raised by our platform's customers to quickly provide access, unblock issues, and provide general guidance on best platform practices and patterns.
7. Collaborate with existing machine learning engineers, data scientists, and ML platform engineers from cross-functional teams.

You Bring:

1. Advanced degree (Master’s or above) in Computer Science, specializing in software engineering or platform engineering.
2. 3 years of industry experience working in an MLOps position.
3. Strong programming skills in languages such as Python, Scala, and Java.
4. Hands-on experience in Databricks, mlFlow, Seldon.
5. Excellent problem-solving skills and analytical skills.
6. Deep knowledge of the AWS ecosystem.
7. Expertise in Git, Docker, Kubernetes, Jenkins, Prometheus, and Grafana.

Preferred Qualifications:

1. Experience in supporting as a platform engineer, large-scale online customer-facing ML applications, preferably recommendation systems.
2. Experience working with custom ML platforms, feature store, and monitoring ML models.
3. Familiarity with best practices in DevOps, MLOps.
4. Knowledge of additional CI/CD tooling such as Prow, Bazel, and ArgoCD.
5. Experience in Snowflake, Kubeflow, Tecton.