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About This Role
About Niyam IT (Niyam)
Founded in 2007 by a team of visionary consultants, Niyam IT was built on the belief that exceptional technology solutions are created through the perfect balance of disciplined processes, innovation, and passion. For nearly 20 years, we have been a trusted partner to the U.S. Federal Government, delivering mission-critical IT solutions that support Emergency Preparedness and Response, Civilian Agencies, Law Enforcement, and Public Safety organizations across the nation.
At Niyam, excellence is more than a goal. It is embedded in everything we do. Our commitment to quality, security, and continuous improvement is demonstrated through our CMMI DEV Level 3 accreditation, ISO certifications (ISO 9001:2015, ISO/IEC 20000-1, and ISO/IEC 27001), and active CMMC Level 2 certification.
We are committed to fostering an exceptional workplace where employees are empowered to grow, innovate, and make a meaningful impact. Niyam is proud to have been recognized by The Washington Post as a Top Workplace for two consecutive years and named to the Inc. 5000 list of America’s Fastest-Growing Private Companies for four consecutive years. These achievements reflect our unwavering commitment to cultivating a culture built on collaboration, excellence, innovation, and the success of our employees.
Join Niyam and become part of a team where your talents help drive meaningful missions that serve and protect communities nationwide.
What We Offer
- Flexible Work Hours: We understand that life extends beyond the traditional workday. Our flexible scheduling options empower you to balance your professional responsibilities while making time for what matters most.
- Remote Work Opportunities: Work where you perform best. Niyam embraces flexibility and offers remote work options that support productivity, collaboration, and work-life integration.
- Professional Growth & Development: At Niyam, you're not just taking a job, you're building a career. We invest in our employees through fully funded training, certifications, mentorship opportunities, and clear pathways for advancement.
- Exceptional People: Our employees are at the heart of everything we do. You'll work alongside talented, supportive, and mission-driven professionals who are passionate about making an impact and helping one another succeed.
- Innovative & Collaborative Culture: We foster an environment where creativity is encouraged, ideas are valued, and teamwork drives success. At Niyam, innovation and collaboration are part of our DNA.
- Commitment to Diversity & Inclusion: We believe our greatest strength lies in our people. Diverse perspectives, backgrounds, and experiences are celebrated, creating a workplace where everyone feels respected, valued, and empowered to contribute their best.
- Meaningful Work with Purpose: Join a team that supports critical federal missions and delivers innovative solutions that make a difference for government agencies and the communities they serve.
Join us in creating a workplace where innovation, diversity, and well-being thrive. Your journey at Niyam awaits. Apply today!
Niyam is seeking an experienced AI/ML Engineerto support one of our federal clients. The ideal candidate for the AI/ML Engineer position will have a strong background in full-stack software development and building innovative AI/ML solutions. They will develop custom applications, integrate AI capabilities such as Google Gemini AI, and work with APIs, databases, and modern programming languages to deliver secure, scalable solutions. This individual will collaborate with data science and prototyping teams to solve complex technical challenges, contribute to Agile development efforts, and support innovative projects for a federal client.
Roles and Responsibilities
- Design, develop, and implement custom software solutions for a variety of AI/ML-related pilot projects and use cases including Google Gemini AI.
- Develop and work with APIs including RESTful services, authentication methods, data formats, and handling API errors.
- Use SQL and NoSQL database including to evaluate and choose the appropriate database type based on the application requirements;
- Integrate SQL and NoSQL databases within the same application, when appropriate; and apply advanced understanding of security best practices for both SQL and NoSQL databases.
- Act as a member of one or more prototyping teams supporting teammates and collaborating to deliver working software applications on short timelines.
- Analyze complex project-related problems and creating innovative solutions involving technology, methodology, tools, and solution components.
- Actively participate in agile delivery phases and ceremonies including release and sprint planning, artifact creation, sprint testing, demonstrations, and retrospectives.
Qualifications and Education Requirements
- US Citizenship with ability to successfully complete a federal background investigation.
- Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or related field (equivalent practical experience may be considered).
- 7+ years of software development experience.
- Ability to analyze technically complex problems and develop and implement new and innovative solutions in a fast-moving and fluid software prototyping development environment.
- Expertise in multiple software developer languages including, but not limited to: YAML, JSON, Python, Java, JavaScript and TypeScript.
- Full Stack development experience including proficiency in both front-end (Angular) and back-end development, ability to handle all aspects of a web application from designing the user interface to managing the server and database.
- Ability to work with Data Scientist teams to integrate applications with AI/ML, Big Data, or BI solutions.
- Ability to work independently on a complex task with little direction and management oversight.
Preferred Skills
- Experience working with live data and video streams.
- Technical certifications such as AWS Certified Developer Associate.
- Experience with DevOps (CICD) solutions such as GitLab.
- Experience with AI/ML solutions or complex solutions for predictive analytics.
- Experience working in a geographically dispersed, remote team.
- Understanding of Data Science principles and best practices.
- Ability to work a hybrid schedule 1-2 days/week.
Why Join Niyam
- Award-Winning Culture: Proudly recognized by The Washington Post as a Top Workplace for two consecutive years and named to the Inc. 5000 list of America’s Fastest-Growing Private Companies for four consecutive years, reflecting our commitment to employee engagement, growth, and excellence.
- Meaningful Mission Impact: Join a small business trusted by federal agencies to deliver innovative solutions that support critical national missions.
- Drive Innovation: Play a key role in shaping the future of Niyam’s proprietary technology accelerators, including GeoCube®, SPHERE®, and RisQ®, which are used to solve complex challenges across the federal government.
- Accelerate Your Career: Benefit from a transparent career framework designed to support continuous learning, professional development, and advancement opportunities, including progression to Distinguished Engineer and other technical leadership roles.
- Collaborative, People-First Environment: Work alongside talented professionals who are passionate about innovation, teamwork, and delivering exceptional results while supporting one another's success.
Join Niyam and help us win the work that matters.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
Niyam IT, Inc. is an Equal Opportunity (“EEO”) Employer. All qualified applicants will receive consideration without regard to race, color, creed, religion, sex, sexual orientation, gender identity, pregnancy, marital status, partnership status, age, citizenship status, veteran or military status, medical condition, genetic information, national origin, disability, unemployment status or any other characteristic prohibited by federal, state and/or local laws.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At NiyamIT, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
NiyamIT AI Hiring
NiyamIT has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Ashburn, VA, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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