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Software Engineer Ai Model Training Jobs in Washington

Advisor Software Engineer (AI/ML)Skip to main contentWhen you visit any website, it may store or ... Experience with model development and deployment practices, including feature engineering, model ...

New

AI/ML Engineer

Fort George G Meade, MD · Hybrid

$99K - $225K/yr

Experience developing andmaintainingAI and ML pipelines for model training, validation, and ... HS diploma or GED and 6+ years of experience with software engineering or AI system development, or ...

AI/ML Engineer

Arlington, VA · On-site

$120 - $180/hr

Develop automated pipelines for model training, validation, testing, deployment, and monitoring ... software engineering, or data science experience * Experience developing and deploying ...

New

Software Engineer (AI/Agentic Systems)

Columbia, MD · On-site

$168K - $199K/yr

Integrate AI models, APIs, and data sources into cohesive, production-ready systems * Build and ... Up to 5 paid training days per year Additional Benefits * Company-provided apparel * Regular ...

Software Engineer - AI

Washington, DC · Remote

$150K - $215K/yr

As a Software Engineer - AI, you'll design and deliver end-to-end generative AI and large language model (LLM) applications that directly power this mission. You'll build AI pipelines and ...

Senior Software Engineer (AI/ML)

Arlington, VA · On-site

$140K - $185K/yr

HOW YOU'LL DRIVE IMPACT * Design and develop machine learning models and applications for ... Professional development (training, certifications, conferences) * Paid cloud developer accounts

The US Census Bureau is looking for a talented AI/ML Software Engineer to join their team for the ... Collaborate with data scientists and engineers to ensure seamless integration of AI models. * Write ...

SME - Data Engineer

Bethesda, MD · On-site

$122K - $146K/yr

They are seeking a Senior Data Engineer to design and implement large-scale data systems and prepare datasets for AI model training. Responsibilities : • Experience in designing and implementing ...

THE IMPACT YOU WILL MAKE The Advisor Software Engineer (AI/ML) role will offer you the flexibility ... Experience with model development and deployment practices, including feature engineering, model ...

Showing results 41-60

Software Engineer Ai Model Training information

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.

What are popular job titles related to Software Engineer Ai Model Training jobs in Washington?

For Software Engineer Ai Model Training jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Software Engineer Ai Model Training jobs in Washington look for?

The top searched job categories for Software Engineer Ai Model Training jobs in Washington are:

What cities in Washington are hiring for Software Engineer Ai Model Training jobs?

Cities in Washington with the most Software Engineer Ai Model Training job openings:

Advisor Software Engineer (AI/ML)

The Fannie Mae

Reston, VA • On-site

$155 - $209/hr

Other

Medical, Life

Posted yesterday

New


Fannie Mae rating

9.0

Company rating: 9.0 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description

Advisor Software Engineer (AI/ML)Skip to main contentWhen you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. This information might be about you, your preferences or your device and is mostly used to make the site work as you expect it and to help give you a more personalized web experience. Because we respect your right to privacy, you can choose not to allow some types of cookies. Click on the different category headings to find out more and change our default settings. However, blocking some types of cookies may impact your experience on the site and the services we are able to offer.Privacy Notice# Search All JobsAdvisor Software Engineer (AI/ML) page is loaded## Advisor Software Engineer (AI/ML)Applyremote type: Flexlocations: Reston, VAtime type: Full timeposted on: Posted 6 Days Agojob requisition id: JR2645Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.Job DescriptionAs a valued contributor to our team, you will design, produce, test, or implement software, technology, or processes across multiple projects, programs, or products, as well as create and maintain IT architecture, large scale data stores, and cloud-based systems.**THE IMPACT YOU WILL MAKE**The Advisor Software Engineer (AI/ML) role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities: * Determine the needs of the customer groups across multiple projects, programs, or products while identifying and resolving conflicting or complementary needs across customer groups.* Design and develop software solutions to meet needs and may also lead matrixed teams.* Apply extensive expertise in process-driven approach in designing solutions.* Implement new software technology and coordinate simultaneous implementation tasks across teams.* Oversee the maintenance of existing softwareThere is 1 opening for this position which can be based in our Reston, VA office.**An Advisor role at Fannie Mae is on the same level as a Manager, but in an IC capacity.****THE EXPERIENCE YOU BRING TO THE TEAM****Minimum Required Experiences*** 6 years of hands-on software engineering experience designing, developing, and maintaining scalable enterprise applications and cloud-native solutions.* Strong proficiency in Python development, including backend services, APIs, automation, data processing workflows, and production-ready AI/ML applications.* Strong skills in system design and architecture, including scalable, resilient, secure, and maintainable solution design.* Experience building API-driven solutions, including REST APIs, microservices, service orchestration, secure API development, and enterprise system integrations.* Hands-on experience with AWS cloud-native development, including serverless, event-driven, containerized, and distributed application patterns.* Experience with SQL and data platforms, including PostgreSQL, Snowflake, or similar relational and analytical database technologies.* Deep understanding of the software development lifecycle, including requirements analysis, design, development, testing, deployment, production support, and maintenance.* Experience with engineering best practices, including secure coding, code reviews, automated testing, CI/CD, observability, performance tuning, and production issue resolution.* Experience collaborating with technical and business stakeholders, including translating business needs into technical solutions and communicating risks, trade-offs, and delivery impacts.**Desired Experiences*** Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology, Data Science, Machine Learning, Artificial Intelligence, or a related field.* Experience designing and delivering AI-enabled enterprise software solutions, including GenAI applications, intelligent automation, AI-assisted workflows, and AI-driven decision support.* Experience with MLOps, vector databases, embedding-based search, MCP-based tool integration, and enterprise AI governance practices.* Experience writing technical papers, invention disclosures, patent-supporting documentation, or reusable engineering playbooks for emerging technology solutions.* Experience with testing strategies and tools, including unit, integration, functional, regression, and performance testing.* Experience with Scaled Agile Framework, Agile methodology, cybersecurity vulnerability remediation, and enterprise delivery practices.* Strong relationship management skills with the ability to collaborate across stakeholders, influence outcomes, and support strategic enterprise technology initiatives.**AWS Cloud Technologies*** Hands-on AWS software engineering experience, including application development using AWS service APIs, AWS CLI, AWS SDKs, and cloud-native deployment patterns.* Hands-on experience with core AWS services, including AWS Lambda, Amazon S3, Amazon EC2, Amazon API Gateway, IAM, CloudWatch, EventBridge, SQS, SNS, and Step Functions.* Experience with AWS AI/ML services, including Amazon SageMaker, Amazon Bedrock, and AWS-based model deployment or inference patterns.* Experience with containers and DevOps practices, including Docker, Kubernetes, ECS/EKS, CI/CD pipelines, automated testing, and release management.* Understanding of cloud security and compliance practices, including IAM, encryption, secrets management, vulnerability remediation, logging, and secure application design.**AI/ML and GenAI Technologies*** Hands-on experience in machine learning, AI engineering, data science, or applied AI solution development.* Hands-on experience with Generative AI and Large Language Models, including OpenAI, Anthropic, Cohere, Amazon Bedrock, or similar enterprise AI platforms.* Strong proficiency in Python and AI/ML libraries, including PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, and related ML frameworks.* Experience building Retrieval-Augmented Generation solutions, including embeddings, vector databases, semantic search, document retrieval, chunking strategies, prompt grounding, and response evaluation.* Experience with LLM application patterns, including prompt engineering, guardrails, model evaluation, tool/function calling, agentic workflows, and responsible AI considerations.* Familiarity with AI application frameworks and tools, such as LangChain, LlamaIndex, FastAPI, MCP tools, vector databases, and API-based AI service integration.* Experience with model development and deployment practices, including feature engineering, model serving, model monitoring, MLOps, and productionizing AI/ML capabilities.**Leadership and Innovation Skills*** Proven experience leading technical delivery within software engineering teams, including solution direction, task assignment, progress monitoring, issue resolution, and delivery accountability.* Experience mentoring and coaching engineers, including technical guidance, code review feedback, design support, and professional development.* Ability to influence technical decisions and engineering practices, including architecture discussions, design trade-offs, quality improvements, and adoption of modern AI/ML and cloud engineering standards.* Experience partnering with product owners, architects, business stakeholders, risk, security, and operations teams to deliver solutions aligned with business outcomes and enterprise standards.* Ability to produce high-quality technical documentation, including architecture papers, solution design documents, technical white papers, AI/ML implementation guides, and executive-ready technical summaries.* Experience contributing to innovation artifacts, such as invention disclosures, patent-supporting technical writeups, proof-of-concept documentation, and publication-ready technical papers when applicable.**Enterprise Risk Technology - Software Engineering - Advisor****155,000.00 - 209,000.00****JR2645**QualificationsAmazon Web Services (AWS), Amazon Web Services (AWS), Atlassian JIRA, AWS Machine Learning, Business Process Management Skills, Cloud Technology, Communicating in Technical Writing, Communication, Computer Vision, Configuration Management (CM), Coordination, Customer and Market Insights, Data Analysis Interpretation, Data Mining, Data Visualization, Enterprise Information Security Architecture, Gradient Boosting Algorithms, Identity Management (IdM), Internal Auditing, Knowledge Management, Machine Learning (AI), Model Explainability, Multi-modal Machine Learning Models, Natural Language Processing (NLP), Neural Networks Methods and Algorithms {+ 20 more}Education:Master's Level Degree: Artificial Intelligence and Robotics (Required)The future is what you make it to be. Discover compelling opportunities at Fanniemae.com/careers.For most roles, employees are expected to work onsite on a regular basis at their designated office location. In-office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity/gender expression, marital or parental status, or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment, unless to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process, please complete this form.The hiring range for this role is set forth below. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being. See more here. #J-18808-Ljbffr

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