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Remote Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Postdoc, and why are they important?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
What are the most commonly searched types of Machine Learning Postdoc jobs in Virginia? The most popular types of Machine Learning Postdoc jobs in Virginia are:
What are popular job titles related to Remote Machine Learning Postdoc jobs in Virginia? For Remote Machine Learning Postdoc jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Virginia look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Virginia are:
What cities in Virginia are hiring for Remote Machine Learning Postdoc jobs? Cities in Virginia with the most Remote Machine Learning Postdoc job openings:
Remote Machine Learning Postdoc jobs near you
Machine Learning Engineer with Security Clearance

Machine Learning Engineer with Security Clearance

NT Concepts

Chantilly, VA • On-site, Remote

Other

Posted 12 days ago

Job description

NTC OVERVIEW: We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. We're looking for the best and the brightest to join us in supporting this mission.

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

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