Machine Learning Operations Engineer- Space Domain Awareness

Trusted Space, Inc.; United States; Remote; USD 125,000 - 150,000; Full time

Job summary

A leading company in the space domain is seeking a Machine Learning Operations Engineer to enhance their ML model training pipeline. The role involves developing computer vision models and requires strong Python and ML framework skills. The position is remote, offering a collaborative environment and competitive benefits.

Benefits

Medical, dental, and vision plans

401(k) plan

Paid holidays and generous paid time off

Short-term and long-term disability insurance

Qualifications

• 3+ years’ experience in the machine learning industry.
• Strong experience in Python and ML frameworks.
• Self-motivated with excellent problem-solving skills.

Responsibilities

• Build and maintain robust computer vision model training pipelines.
• Develop and optimize computer vision models for space domain awareness.
• Automate data labeling pipelines.

Skills

Python

Problem Solving

Innovation

Education

Bachelor’s or Master’s degree in computer science

Tools

PyTorch

Keras

Tensorflow

Azure Machine Learning Studio

AWS SageMaker

Google Vertex AI

MLflow

Kubeflow

Docker

Kubernetes

Job description

Machine Learning Operations Engineer - Space Domain Awareness (Remote)

Position Title: Machine Learning Operations Engineer- Space Domain Awareness
Requisition ID: TA166
Location: Remote
Application Deadline: We are accepting applications on an ongoing basis

Who We Are
Trusted Space builds solutions both on the ground and in space. Our solutions provide advanced capabilities supporting missions vital to our Nation’s defense, intelligence, and science sectors. Our diverse talented staff of scientists, engineers, and business professionals support critical missions including Space Domain Awareness, Battlespace Awareness & Decision Support, Space Exploration & Science, and the establishment of core Space Infrastructure.

Our Culture
As a customer-focused service provider, Trusted Space values it’s employees and clients. We live by our values; central to this principle is the concept to treat others as you would like other to treat you. We offer a collaborative and supportive work environment, world class benefits, and work-life balance. We encourage life-long learning and continuous improvement in all that we do. Each day, we seek to be better than the previous day, embracing our journey to Excellence. We consider it a privilege to work with our customers on their greatest challenges.

Job Description
About the Role
Trusted Space is seeking an experienced Machine Learning Engineer to rapidly improve and scale our prototype ML model training pipeline, including the addition of data labeling capabilities. The ideal candidate is comfortable working in fast-paced, small cross-disciplinary remote teams that rapidly matures tools for the US Warfighter. This position will be Remote.

What you'll do:

• Build and maintain a robust computer vision model training pipelines
• Build and automate data labeling pipelines
• Develop and optimize computer vision models for space domain awareness
• Stay abreast of the latest advancements in AI and ML and apply this knowledge to improve our models and methodologies.

Qualifications

• This position requires the candidate to be a United States Citizen.
• Bachelor’s or Master’s degree in computer science, machine learning, or a related field
• 3+ years’ experience in the machine learning industry
• Strong Experience in Python and ML Frameworks (PyTorch, Keras, Tensorflow)
• Strong Experience with DevOps and MLOps practices
• Experience with machine learning platforms such as Azure Machine Learning Studio, AWS SageMaker, Google Vertex AI or other
• Experience in experiment tracking toolsets like MLflow, Kubeflow
• Previous experience with distributed model training
• Self-motivated with a willingness to take ownership of tasks
• Excellent problem-solving skills and a passion for innovation

Desired Skills

• Experience in the aerospace industry
• Experience with space imagery datasets (EO/IR Imagery, radar)
• Experience with hyperparameter tuning frameworks like Optuna or Ray Tune
• Previous experience in data labeling/auto labeling toolsets
• Experience with containerization tools like docker and orchestration frameworks like Kubernetes.
• Bonus: Experience in Deep Reinforcement Learning and libraries like RLib and Stable Baselines

Salary Range: The salary range for this role is $125,000-$150,000. Please note that this range is a general guideline and can vary.Trusted Space, Inc. considers several factors when extending an offer including, but not limited to: scope, location, position responsibilities, education/training, key skills and business considerations.

Benefits: Trusted Space seeks to create an environment where Employees are empowered and supported to achieve their full potential. We encourage life-long learning within our Agile & Innovative work environment. We offer competitive compensation and benefits including medical, dental, and vision plans; life and accidental death & dismemberment insurance; 401(k) plan; paid holidays and generous paid time off; short-term and long-term disability insurance; and other benefits to promote health, wellness, and a positive work-life balance.

Trusted Space, Inc. is an Equal Opportunity Employer. We do not discriminate based on race, religion, color, sex, gender, gender identity, sexual orientation, age, marital status, national origin, veteran status, or any other status protected under federal, state, or local law. All aspects of employment are decided based on qualifications, merit, competence, performance, and business need.

Trusted Space, Inc. participates in the E-Verify program.

DISCLAIMER: Trusted Space, Inc. only uses the respective domains of trustedspace.com and trustedspace.us for official contact and any other domains are likely a scam and do not originate from our company.Trusted Space will never ask a candidate for access or pass codes to personal accounts including e-mails, bank accounts, CashApp, Paypal, Venmo, etc.

This is a full time position

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