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Senior Machine Learning Engineer



11d ago

  • Job
    Senior (5-8 years)
  • Data
  • Toronto

AI generated summary

  • You should have 5+ years in ML infrastructure, strong skills in ML foundations, frameworks, Python & Java, BS/MS/PhD in CS, & experience collaborating with data scientists and business analysts.
  • You will lead ML initiatives, fine-tune models, design frameworks, implement benchmarks, and collaborate with teams to improve ML capabilities at Snowflake.


  • Have 5+ years of industry experience designing and building infrastructure, machine learning platforms, machine learning services and frameworks.
  • Strong knowledge of Machine Learning foundations, neural networks, statistics and optimization
  • Strong track record of working with machine learning systems and/or platforms.
  • Experience with several of the following frameworks: Pandas, NumPy, SKLearn, XGBoost, LightGBM, PyTorch, Tensorflow, Keras.
  • Fluent in both Python and Java.
  • Have worked well with data scientists, business analysts and machine learning infrastructure to connect the dots between science, business and technology partners.
  • BS/MS/PhD in Computer Science or related majors, or equivalent experience


  • Help define and own the roadmap for ML & AI for Marketplace Trust, working collaboratively and proactively with senior architects, PMs and team leadership. The initiatives include platforms and tools that review, moderate, approve and modify content on Snowflake Data Marketplace platform
  • Investigate, evaluate, compare and fine-tune multiple Large Language Models (LLM) to deliver maximum value to Snowflake’s customers
  • Design, build and maintain experimentation framework
  • Help define and implement benchmarks and metrics for model performance
  • Define and implement experimentation-to-production process
  • Own production ML Ops, metrics, monitoring, alarming and logging
  • Collaborate across other engineering partner teams to continuously improve ML development velocity and capabilities at Snowflake.
  • Support team members in delivering a high level of technical quality.


What are the key responsibilities of a Senior Machine Learning Engineer at Snowflake?

As a Senior Machine Learning Engineer at Snowflake, your key responsibilities will include understanding the platform architecture, harnessing AI to improve content quality and increase customer trust, defining strategies, setting technical directions, designing and executing projects, engaging in innovation, and unlocking the power of data for AI for thousands of customers.

What qualifications and skills are required for this role?

To be successful as a Senior Machine Learning Engineer at Snowflake, you should have a strong background in machine learning, AI, data science, or a related field. Proficiency in programming languages such as Python, Java, or Scala is essential. Experience with cloud platforms, big data technologies, and deep learning frameworks is also desirable.

What opportunities for career growth and development are available for Senior Machine Learning Engineers at Snowflake?

As a Senior Machine Learning Engineer at Snowflake, you will have opportunities for career growth and development through continuous learning, training, and mentoring programs. You will also have the chance to work on cutting-edge projects, collaborate with top talent in the industry, and contribute to shaping the future of AI in data analytics.

Snowflake delivers the Data Cloud — mobilize your data with near-unlimited scale and performance.

Founded Year

Mission & Purpose

Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the Data Cloud.