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Selected role

Machine Learning Engineer [Remote]

Braintrust CA San Francisco, California, United States

$98k - $108k Senior Full-time

JOB TYPE: Freelance, Contract Position (no agencies/C2C - see notes below)
LOCATION: Remote - United States and canada only
HOURLY RANGE: Our client is looking to pay $110-$140/hr
ESTIMATED DURATION: 40h/week - long-term, ongoing project

THE OPPORTUNITY

Senior Software Engineer - Machine Learning Platforms

The client is a leader in the e-commerce space for all things home. Our community of Engineers are obsessed with using data and technology to ensure our customers can build a home that they love. Our platforms support millions of people searching every day for the perfect item, and provide a unique purchase and delivery experience. Come help us innovate and grow to our next $10B in revenue!

We are looking for an experienced Senior Software Engineer to join our Machine Learning Platforms team that is building cutting edge platforms that will enable us to deliver world class ML solutions that are helping serve our customers across their journey with us. The work includesm but is not limited to the intricacies involved in developing scalable platform capabilities for feature management, model training and deploying models across a range of business functions. In a nutshell these platforms power the model development lifecycle and cater to the diverse use cases across our global community of hundreds of data scientists.

We’re looking for someone who not only enjoys writing code and seeing their ideas come to fruition on a global scale, but is also able to upskill the engineers around them through leading by example. In this role, you will be leading the development of cloud native capabilities to ensure our Data Scientists can focus on model development and delivering cutting edge intelligent solutions.

What You'll Do:

● Drive and own the delivery of Machine Learning platforms from design and architecture to production
● Leverage your deep knowledge of distributed systems engineering to build next generation Machine Learning capabilities
● Design scalable systems using Python, Go, Kubernetes, Kafka, GCP, Airflow, and other technologies
● Think outside of the current technology/stack limitations to push the boundaries on what is possible and deliver feasible solutions collaboratively
● Champion open source solutions and Google Cloud native technologies, and their application to our use cases
● Develop end to end ML pipelines that can power the full range of Machine Learning initiatives
● Partner with product leaders to understand technical pain points for data scientists and other engineers and translate them into clear and robust engineering solutions
● Advise engineering and product management on technical roadmap, ensuring that the vision aligns with broader company objectives
● Promote a culture of engineering excellence and strengthen the technical expertise of our engineering and product teams Senior Software Engineer,Machine Learning Platforms
● Keep current on ML engineering technology trends, evaluate, work on proof-of-concept and make recommendations on the technologies based on their merit

Who you are:

● 5+ years of experience in software engineering and designing systems at scale
● 3+ years of experience in Linux-based development, and Python/Go development while leading engineering teams
● Experience developing data pipelines, and orchestrating deployments, including experience with Kubernetes
● Strong understanding of containerization (Docker, etc.), and associated software engineering best practices
● Excellent communication skills with demonstrated experience driving teams forward and ability to influence technical decisions to line up with the company’s strategy
● Hands-on experience driving software development within high-growth environments at scale
● Excellent organizational, analytical, and hypothesis- driven critical thinking skills to transform data into actionable insights

Nice to Have:
● Mix of start-up and large-company experience working on Machine Learning solutions
● Familiarity with ML platforms (opensource or offered by Google Cloud) and how to implement them on a large scale
● Familiarity with ML experiment management tools like MLFlow and ML orchestration and pipelines with experience in either Airflow, Kubeflow

Apply Now!

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