Remote Unique Learning System Jobs in Virginia (NOW HIRING)

If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, join our growing team and discover What's Next for you. Mission Focus: As a Machine Learning Engineer, you will have the unique opportunity to support research, design, and implement cutting edge algorithms for a program focused on building robust computer vision algorithms. This requires coding in Python with PyTorch, implementing and maintaining development environments and supporting ML tools, such as Kubeflow and MLFlow.

Additionally, you will contribute to the program's source code, implementing data science techniques. Our delivery teams are driven to explore new ideas and technology, and care deeply about collaboration, feedback, and iteration. We follow modern agile practices, embrace the Ops ethos (DataOps/DevSecOps/MLOps) to "automate-first", use modern tech stacks, and constantly challenge each other to grow and improve.

If cutting edge data science projects resonate with you, and you care deeply about joining a mission-driven company with a strong growth direction and diverse culture, we'd love to learn more about you. Check out the details below, and let's connect. Technical members of our solutions teams require little guidance, but love to learn, collaborate, and problem solve.

This position requires mid to senior level of experience, a passion for mission support, and a strong desire to solve our customers' hardest technical and data challenges. Clearance: TS/SCI Clearance required. Location/Flexibility: Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems at scale.

You'll implement computer vision machine learning applications using existing and emerging technology platforms to deliver business value to our clients. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You'll also mentor other engineers and develop your technical knowledge and skills to keep our team at the cutting edge of technology.

* Collaborate with a cross-functional team comprising other ML Engineers, Software Engineers, DevSecOps Engineers, and Data Scientists. * Develop machine learning models and pipelines that are integral to mission success within this computer vision platform. Qualifications: * 4+ years of relevant hands-on experience developing and implementing ML algorithms * Practical experience training and deploying Machine Learning models.

Ideal candidate would have experience with PyTorch, NumPy, TensorFlow, VS Code) * Understanding of machine learning techniques and algorithms, data mining, and statistical analysis. * Experience with cloud platform (AWS, Azure and GCP), AWS experience preferred * Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevSecOps specifically GitLab CI/CD * Experience building and maintaining machine learning pipelines * Experience with container applications such as Docker, Kubernetes, OpenShift. Kubernetes is preferred * Practical programming and scripting skills (Python preferred) * Understanding of data structures, data modeling and software architecture.

* A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams * Experience with synthetic data generation for training and evaluation of ML Models is a plus * Experience working with customers to better optimize their ML objectives * Fast learner, analytical thinker, creative, hands-on, strong communication skills * Able to work both independently and as part of a team * Excellent problem-solving skills and attention to detail * Experience working with LLMs for problem solving and code production in a safe and responsible manner Physical Requirements: * Prolonged periods sitting at a desk and working on a computer. * Must be able to lift up to 10-15 pounds at times. #JT