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Remote Machine Learning Postdoc Jobs in Maryland

Lead Data Engineer

Baltimore, MD · On-site +1

$113K - $136K/yr

... machine learning roles. * Strong proficiency in Snowflake tech, DBT, Airflow, Python, Java ... Work Flexibility This role is eligible for full time remote work.

This is a full-time position located at the NIH campus in Bethesda, MD and/or remote. The National ... machine learning, multiple clouds) serve more users than almost any other US Government Agency ...

This opportunity is full time and onsite at the NIH-NCBI in Bethesda, MD and/or remote work. NCBI ... machine learning, multiple clouds) serve more users than almost any other US Government Agency ...

CNO Developer

Annapolis, MD · On-site +1

$86K - $198K/yr

... and machine learning to influence the delivery of your work. Using your network operations ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

Showing results 41-60

Remote Machine Learning Postdoc information

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 the key skills and qualifications needed to thrive as a remote machine learning postdoc?

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 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 Maryland?

The most popular types of Machine Learning Postdoc jobs in Maryland are:

What job categories do people searching Remote Machine Learning Postdoc jobs in Maryland look for?

The top searched job categories for Remote Machine Learning Postdoc jobs in Maryland are:

What cities in Maryland are hiring for Remote Machine Learning Postdoc jobs?

Cities in Maryland with the most Remote Machine Learning Postdoc job openings:

Lead Data Engineer

T Rowe Price

Baltimore, MD • On-site, Remote

$113K - $136K/yr

Full-time

Re-posted 21 days ago


T. Rowe Price rating

9.1

Company rating: 9.1 out of 10

Based on 21 frontline employees who took The Breakroom Quiz


Job description

Role Summary
T. Rowe Price is seeking an experienced Lead Data Engineer to guide the development and deployment of Enterprise data solutions that drives transformation enabling new business capabilities driving growth, tangible operational efficiency, and superior client experiences. The successful candidate will be a hands-on leader with deep technical skills, who can drive best practices and innovation in a collaborative, purpose-driven environment.

Responsibilities

  • Lead the design, development, and maintenance of Enterprise data platform and solutions, analytics capabilities including modernizing data supply chain, integrating advanced data governance capabilities and data distribution patterns.
  • Collaborate with data engineers, business partners, product owners, and other stakeholders to understand business requirements and develop them into robust enterprise data solutions.
  • Modernize legacy ETL capability to data supply chain solution integrating with Enterprise data platform to provide scalability.
  • Modernize legacy data quality, data governance capabilities to innovative enterprise capabilities that can scale.
  • Champion data governance, security, and regulatory compliance, ensuring alignment with T. Rowe Price's standards and industry best practices.
  • Mentor and develop junior engineers, fostering a culture of innovation, diversity, and continuous improvement.
  • Lead offshore team effectively to ensure delivery success aligning to business & strategic objectives.
  • Evaluate and implement emerging technologies, frameworks, and tools to advance T. Rowe Price's data and AI capabilities.
  • Troubleshoot and optimize data solutions and platform performance, ensuring scalability and resilience.
  • Document system architectures, processes, and best practices for technical and non-technical stakeholders.

Qualifications

Required:

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)
  • 8+ years of professional experience in data engineering, AI, or machine learning roles.
  • Strong proficiency in Snowflake tech, DBT, Airflow, Python, Java.
  • Experience with cloud data platforms (AWS, Snowflake), preferably within a regulated industry.
  • Solid understanding of Agile methodologies and DevOps practices.
  • Excellent communication, collaboration, and leadership skills.
  • Knowledge of data privacy, compliance (e.g., GDPR), and industry regulations relevant to financial services.
  • Experience in the asset management or financial services industry.
  • Familiarity with CI/CD pipelines, and model lifecycle management.

Preferred:

  • Industry certifications in cloud or data engineering technologies.
  • Knowledge of data privacy, compliance (e.g., GDPR), and industry regulations relevant to financial services.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for full time remote work.


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