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Remote Machine Learning Postdoc Jobs in Washington, DC

West 4th Strategy

Data Scientist (Remote)

Washington, DC · On-site +1

$135K - $150K/yr

Build and implement machine learning models and/or predictive analytics. * Maintenance of ... Remote - Eastern Standard Time zone - preferred but not required CLEARANCE * U.S. Citizenship ...

BluePath Labs

AI Developer - Remote

Washington, DC · Remote

$110K - $160K/yr

Remote (occasional travel may be required) Clearance:Public Trust or able to obtain Salary: $110 ... The AI Developer will design, build, and support artificial intelligence and machine learning ...

BluePath Labs

AI Developer - Remote

Washington, DC · Remote

$110K - $160K/yr

Remote (occasional travel may be required)Clearance:  Public Trust or able to obtain  Salary ... and machine learning solutions that address complex business and mission challenges. The role ...

BluePath Labs

AI Developer - Remote

Washington, DC · On-site +1

$110K - $160K/yr

Remote (occasional travel may be required) Clearance: Public Trust or able to obtain Salary: $110 ... The AI Developer will design, build, and support artificial intelligence and machine learning ...

Maximus

Data Scientist (Remote)

VA · On-site +1

General information Job Posting Title Data Scientist (Remote) Date Tuesday, August 4, 2026 City ... NLP, and machine learning (both supervised and unsupervised) to improve relevance and ...

1872 Consulting

NLP Developer

Herndon, VA · On-site +1

Desired Skills:8+ years of hands-on experience as a machine learning engineer or data scientist.Ph.D./Master's degree in the previously mentioned fields.Experience working with remote sensing data ...

1872 Consulting

NLP Developer

Herndon, VA · On-site +1

Desired Skills:8+ years of hands-on experience as a machine learning engineer or data scientist.Ph.D./Master's degree in the previously mentioned fields.Experience working with remote sensing data ...

ASSYST, Inc.

Software Developer

Sterling, VA · Remote

Develop prototypes and systems leveraging AI and Machine Learning for client projects and internal ... Remote work is not permitted. ASSYST Benefits: We are proud to offer a robust benefits package ...

Sparibis

Azure Data Architect

Washington, DC · On-site +1

$72.25 - $92.75/hr

Location: 100% Remote. This is a United States based position, and candidates must reside in the ... Expertise in statistical modeling, machine learning algorithms, and data mining techniques. * Must ...

ASSYST, Inc.

Software Developer

Sterling, VA · Remote

Develop prototypes and systems leveraging AI and Machine Learning for client projects and internal ... Remote work is not permitted. ASSYST Benefits: We are proud to offer a robust benefits package ...

Knexus

AI Software Engineer (Remote)

Vienna, VA · Remote

This is a fully remote position for candidates in the continental U.S., with work hours aligned to ... This role involves leveraging cutting-edge technologies, including GenAI and machine learning ...

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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 Washington, DC?

The most popular types of Machine Learning Postdoc jobs in Washington, DC are:

What are popular job titles related to Remote Machine Learning Postdoc jobs in Washington, DC?

For Remote Machine Learning Postdoc jobs in Washington, DC, the most frequently searched job titles are:

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The top searched job categories for Remote Machine Learning Postdoc jobs in Washington, DC are:

Remote Machine Learning Postdoc jobs near you

Senior AI/ML Lead/ Developer (Remote)

Cognizant Technology Solutions

Washington, DC • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

Cognizant rating

7.2

Company rating: 7.2 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

53rd of 72 rated business consultants

Job description

Job Summary
We are seeking a highly skilled and innovative Senior AI/ML Engineer with strong expertise in Python, PySpark, Azure Machine Learning, Generative AI, and Full Stack Development to design and deliver advanced analytics and AI-driven solutions for global investment banking and brokerage operations.
The ideal candidate will combine deep technical expertise in machine learning, distributed computing, cloud-native AI platforms, and modern AI frameworks such as LangChain, LangGraph, RAG, Agentic AI Frameworks, FastAPI, and Azure OpenAI Service. This role requires close collaboration with business stakeholders to transform complex financial data into actionable insights that improve decision-making, reduce operational risk, and enhance operational efficiency.
Key Responsibilities
Machine Learning & Advanced Analytics
  • Design, develop, and deploy advanced machine learning models using Python and PySpark to analyze large-scale financial datasets and generate actionable business insights.
  • Build predictive, classification, clustering, anomaly detection, forecasting, and risk models supporting investment banking and brokerage functions.
  • Perform rigorous model validation, back-testing, and experimentation using historical and simulated market data.
  • Evaluate and implement appropriate statistical, machine learning, deep learning, and AI techniques based on business requirements and regulatory considerations.
  • Optimize model performance through feature engineering, hyperparameter tuning, algorithm enhancements, and distributed computing techniques.

Generative AI & Agentic Solutions
  • Design and implement enterprise-grade Generative AI solutions using Azure OpenAI Service.
  • Build and deploy Retrieval-Augmented Generation (RAG) applications leveraging vector databases and knowledge retrieval systems.
  • Develop intelligent agent-based systems using LangChain, LangGraph, and Agentic AI frameworks to automate business workflows and enhance decision support.
  • Apply Natural Language Processing (NLP), Large Language Models (LLMs), document intelligence, and conversational AI to streamline surveillance, reporting, compliance, and advisory functions.
  • Ensure safe, responsible, and governed adoption of Generative AI capabilities across the organization.

Python Full Stack Development
  • Design and develop scalable backend services and APIs using FastAPI.
  • Build microservices and AI application frameworks that integrate machine learning and GenAI capabilities into enterprise ecosystems.
  • Develop reusable and maintainable software components following modern software engineering best practices.
  • Implement API integrations, authentication mechanisms, monitoring, logging, and performance optimization strategies.

Data Engineering & MLOps
  • Design and implement scalable data pipelines and feature engineering workflows using Azure Machine Learning and cloud-native services.
  • Build reusable data products and machine learning components supporting multiple analytics and AI initiatives.
  • Partner with Data Engineering teams to operationalize machine learning models and AI applications.
  • Establish model monitoring, retraining strategies, experiment tracking, and lifecycle management processes.
  • Ensure solutions are secure, reliable, scalable, and production-ready.

Cloud & Azure AI Platform
  • Develop end-to-end ML and AI solutions using:
    • Azure Machine Learning
    • Azure OpenAI Service
    • Azure Data Lake
    • Azure Databricks
    • Azure Storage Services
    • Azure DevOps
  • Manage model deployment, monitoring, governance, and operationalization on Azure platforms.
  • Support enterprise-scale AI and analytics workloads while maintaining compliance and security standards.

Business Collaboration
  • Collaborate with product owners, business analysts, operations teams, and technology stakeholders to define high-value data science initiatives.
  • Translate complex investment banking and brokerage business challenges into measurable analytical solutions.
  • Present recommendations and analytical findings to both technical and non-technical audiences.
  • Drive adoption of AI and machine learning solutions through effective communication and stakeholder engagement.

Governance & Responsible AI
  • Promote responsible AI practices by evaluating model fairness, explainability, bias, security, and data quality.
  • Document assumptions, risks, methodologies, and limitations in a transparent and accessible manner.
  • Ensure adherence to regulatory requirements, model governance frameworks, and enterprise AI policies.

Leadership & Mentoring
  • Mentor junior data scientists, machine learning engineers, and developers.
  • Promote best practices in software development, experimentation, MLOps, AI engineering, and model governance.
  • Contribute to a culture of innovation, continuous learning, and technical excellence.

Required Qualifications
Technical Skills
  • 8+ years of experience in Data Science, Machine Learning, AI Engineering, or related fields.
  • Expert-level proficiency in Python and PySpark for large-scale data processing and model development.
  • Strong experience with:
    • FastAPI
    • REST APIs
    • Microservices Architecture
    • Object-Oriented Programming
    • Software Engineering Best Practices
  • Hands-on experience with:
    • LangChain
    • LangGraph
    • RAG Architectures
    • Agentic AI Frameworks
    • LLM Application Development
  • Strong expertise in:
    • Azure Machine Learning
    • Azure OpenAI Service
    • Azure Databricks
    • Azure Data Lake
    • MLOps and CI/CD Practices
  • Experience developing and deploying enterprise-grade AI/ML solutions in cloud environments.

Machine Learning & AI
  • Deep understanding of:
    • Supervised Learning
    • Unsupervised Learning
    • Deep Learning
    • Ensemble Methods
    • NLP
    • Time-Series Forecasting
    • Anomaly Detection
    • Risk Modeling
  • Strong understanding of model evaluation, feature engineering, experimentation, validation, and explainability.

Domain Experience
  • Prior experience supporting:
    • Investment Banking
    • Capital Markets
    • Brokerage Operations
    • Trade Surveillance
    • Risk Management
    • Front Office or Middle Office Functions
  • Understanding of financial products, market data, and regulatory expectations is highly desirable.

Soft Skills
  • Excellent communication and stakeholder management skills.
  • Ability to explain complex technical topics to non-technical audiences.
  • Strong analytical and problem-solving capabilities.
  • Experience working effectively within distributed and hybrid teams.

Preferred Qualifications
  • Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, or ChromaDB.
  • Knowledge of containerization technologies including Docker and Kubernetes.
  • Experience with CI/CD pipelines and DevOps practices.
  • Exposure to Responsible AI, Model Risk Management, and AI governance frameworks.
  • Azure certifications in AI, Data Science, or Machine Learning.

*Please note this role is not able to offer visa transfer or sponsorship now or in the future*
We're excited to meet people who share our mission and who can make an impact in a variety of ways. Don't hesitate to apply-even if you only meet the minimum requirements. Think about your transferable experiences and unique skills that make you stand out.
Salary and Other Compensation:
Applications will be accepted until Sept 07, 2026,
The annual salary for this position is between $ 90,000 - $ 150,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

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