Interested in this AI/ML Engineer role at Savannah River Mission Completion?
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About This Role
Overview:
Savannah River Mission Completion (SRMC) is seeking an AI /ML Developer or Engineer to be based in our Aiken, SC location on the Savannah River Site.
The AI /ML (Artificial Intelligence / Machine Learning) Developer or Engineer is responsible for designing, developing, implementing, and maintaining the infrastructure, systems, and solutions required for data storage, processing, analysis, and the deployment of AI/ML models. These roles work closely with cross\-functional teams to enable data\-driven decision\-making, create intelligent systems, ensure the quality of data, and drive business innovation.
Responsibilities:
- Develop and implement AI/ML solutions in business environments, ensuring scalability, reliability, and security
- Design, develop, and maintain data pipelines that extract, transform, and load data from various sources into appropriate data storage systems
- Optimize AI/ML models for performance, scalability, and accuracy, considering computational resources and memory constraints
- Collaborate with data scientists, software engineers, and other stakeholders to integrate AI capabilities into existing systems and workflows
- Ensure data consistency and integrity during integration processes, performing data validation and cleaning as needed
- Preprocess, clean, and transform data to ensure quality and relevance for AI/ML model training and inference
- Monitor and tune data systems to identify and resolve performance bottlenecks
- Stay updated with the latest advancements in AI/ML and data engineering technologies to adopt best practices within the team
- Implement data quality checks and validations within data pipelines
- Establish and govern data and algorithms used for analysis, analytical applications, and automated decision\-making
- Other duties as assigned.
Candidate(s) selected to receive an offer will be offered the position level commensurate with their education, experience, and qualifications.
Additional Information
The duties and responsibilities of this position require access to the Savannah River Site (SRS) IT computer network. DOE\-NNSA requires SRMC employees to have U.S. citizenship in order to access the SRS IT computer network system.
Qualifications:
- Bachelor’s degree in Computer Science or related degree; or
- Associate's degree in Computer Science or related degree with relevant practical experience\*; or
- High school diploma or GED with relevant practical experience\*
- Relevant practical experience includes AI data science, ML engineering, software engineering, data analytics, or data mining
Additional Information:
Candidate(s) selected to receive an offer will be offered the position level commensurate with their education, experience, and qualifications.
Preferred Qualifications:
- Experience in AI data science, ML engineering, software engineering, or data analytics
- Experience designing and implementing AI/ML solutions with a focus on machine learning, recommendation systems, pattern recognition, NLP, or data mining
- Experience on projects involving big data processing and distributed computing frameworks such as Apache Spark
- Experience developing and maintaining data lakes, lake houses, etc…
- Expert knowledge of machine learning techniques
- Proficiency in programming languages such as Python, R, JavaScript, Java, and C\+\+
- Knowledge of popular machine learning frameworks
- Familiarity with the Azure cloud platform and relevant AI services
- Familiarity with data engineering concepts, including data pipelines, data integration, data warehousing, and modern data architectures
- Experience with database technologies
- Ability to work with large datasets and perform data cleaning, transformation, and manipulation
- Strong analytical and creative problem\-solving skills
- Ability to effectively communicate technical information to both technical and non\-technical stakeholders
- Adaptability and willingness to learn new AI/ML and data engineering technologies and techniques
- Strong business acumen and interpersonal skills to work across business lines
About:
Savannah River Mission Completion (SRMC), a prime contractor for the US Department of Energy, is responsible for managing the Department of Energy’s Savannah River Site’s Liquid Waste operations contract. Located in Aiken, South Carolina, SRMC is a limited liability company formed by nuclear operations and environmental remediation global leaders BWXT, Amentum, and Fluor. The SRMC Team is responsible for the closure of waste tanks, the operation of the Savannah River Site’s Defense Waste Processing Facility, tank farm operations and associated production and disposal facilities. https://www.savannahrivermissioncompletion.com
Benefits:
Savannah River Mission Completion offers a competitive and comprehensive benefits package with flexibility to meet your needs.
Highlights of our plans include:
- 401k Retirement Savings Plan – 5% immediate company contribution, additional matching for employee contributions
- Health Insurance \& Prescription Drug Program
- Health Savings Account
- Telehealth with BlueCare on Demand
- Dental Coverage
- Vision Coverage
- Flexible Spending Accounts
- Includes 160 hours annual paid time off (accrued monthly), plus 11 paid holidays
- Paid Parental Leave
- Life and Accident Coverage
- Disability Coverage
- Employee Assistance Program
- Tuition Reimbursement
Minimum Pay: USD $62,000\.00/Yr. Maximum Pay: USD $188,000\.00/Yr. Pay Disclaimer: Exceptions to this range/rate may be applied on a case\-by\-case basis taking into account aspects such as education, experience, and skill need of the organization. EEO Statement:
SRMC is committed to equal employment opportunity to employees and qualified applicants regardless of their race, color, religion, gender, national origin, age, physical or mental disability, veteran status, status as a parent, sexual orientation, or genetics. Our equal employment opportunity policies encompass all aspects of the employment relationship, including application and hiring, promotion and transfer, selection for training opportunities, wage and salary administration.
Salary Context
This $62K-$188K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Savannah River Mission Completion, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($125K) sits 42% below the category median. Disclosed range: $62K to $188K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Savannah River Mission Completion AI Hiring
Savannah River Mission Completion has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Aiken, SC, US. Compensation range: $188K - $188K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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