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Manager Spacex Machine Learning Jobs in Utah (NOW HIRING)

They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new ...

A Machine Learning Engineer helps our learners discover content that is relevant to their interests ... Collaborate with Product Managers and UX Designers to better understand the customer, provide ...

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... As an example, we manage catalog data imported from hundreds of retailers, and we build product and ...

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Manager Spacex Machine Learning information

What is the difference between Manager Spacex Machine Learning vs Data Scientist Spacex?

AspectManager Spacex Machine LearningData Scientist Spacex
CredentialsAdvanced degrees in CS, ML, or related fields; leadership experienceDegree in CS, Data Science, or related fields; strong analytical skills
Work EnvironmentTeam leadership, project management, strategic planningData analysis, model development, experimentation
Industry UsageOversees ML teams, manages projects, aligns with business goalsBuilds models, analyzes data, provides insights

The main difference is that the Manager Spacex Machine Learning focuses on leading teams and managing ML projects, while the Data Scientist Spacex primarily develops models and analyzes data to support engineering and business decisions.

What are the most commonly searched types of Spacex Machine Learning jobs in Utah? The most popular types of Spacex Machine Learning jobs in Utah are:
What cities in Utah are hiring for Manager Spacex Machine Learning jobs? Cities in Utah with the most Manager Spacex Machine Learning job openings:

Machine Learning Engineer

Leash Bio

Salt Lake City, UT โ€ข On-site

Full-time

Re-posted 28 days ago


Job description

Job Summary:
Leash Biosciences is at the forefront of integrating machine learning with drug discovery, aiming to revolutionize medicinal chemistry. They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new therapies for devastating diseases.
Responsibilities:
โ€ข Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling.
โ€ข Scale and maintain machine learning model training processes, with a focus on cloud environments (primarily Google Cloud, with flexibility to other platforms).
โ€ข Collaborate closely with ML researchers, data scientists, and lab automation teams to ensure seamless integration of lab data and ML model training.
โ€ข Innovate and iterate on our existing technology stack, taking the initiative to solve problems and improve our ML operations.
โ€ข Act as a self-sufficient project manager, overseeing your projects from conception to completion.
Qualifications:
Required:
โ€ข Strong experience in machine learning engineering, including data handling, model training, and scaling in cloud environments.
โ€ข Comfortable building ML infrastructure
โ€ข Experience working with large amounts of text data, NLP, or training LLMs
โ€ข Demonstrated capability to make informed decisions, take ownership of solutions, and drive projects forward in a startup environment.
โ€ข Excellent collaboration skills, with the ability to work effectively with cross-functional teams.
Preferred:
โ€ข Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker, MLflow, Kubeflow, W&B, Ray, etc.)
โ€ข Ability to manage own compute cluster
โ€ข Ability to maximize GPU utilization and keep cluster busy 24/7
โ€ข Ability to analyze model results and kick off new experiments in response
โ€ข Experience with BERT or similar language models in PyTorch.
โ€ข Experience or interest in biology, chemistry, or related fields is a plus.
Company:
Leash Bio uses AI and machine learning to innovate drug design and medicinal chemistry. Founded in 2021, the company is headquartered in Salt Lake City, USA, with a team of 2-10 employees. The company is currently Early Stage.