Interested in this AI/ML Engineer role at Tempus Unlimited?
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About This Role
Tempus Unlimited, Inc. is a nonprofit organization that provides community-based services to empower children and adults with disabilities to live as independently as possible in the least restrictive environment. The agency, through its programs and services, encourages the inclusion of people with disabilities into the mainstream of society, including social, recreational, family and work activities.
Under limited supervision the Artificial Intelligence (AI) Engineer performs maintenance and quantization's of AI models to deploy at scale to solve real world problems. Software engineering and product development tuning for production ready applications. The AI engineer’s role is to ensure that Tempus Unlimited in-house AI system is secure, functioning at peak levels and using the most up to date hardware and software available.
- Salary $100,000.00 - $140,000.00
- Fully remote in these states only:
- Massachusetts (MA)
- Florida (FL)
- Ohio (OH)
- Pennsylvania (PA)
- Core hours:
- Monday - Friday
- 8:30am to 4:30pm
- Possible after hours depending on need of project
Essential Functions
- Design and build LLM-Powered applications, Api's and agentic pipelines
- Work with network and system administrators to integrate AI models into production systems via REST API's & SDKS
- Develop RAG (Retrieval-Augmented Generation) systems and semantic search features
- Fine-tune foundation models for specific use cases
- Model Development, Train, Evaluate and iterate on ML models using real-world datasets. Contribute to and maintain system standards
- Run track metrics and benchmark model performance
- Optimize and quantize models for latency and accuracy in production
- Build and maintain data pipelines that feed AI models
- Setup Monitoring alerting and logging for model health and drift
- Work with managers and system admins to define AI feature requirements and translate business problems into AI/ML solution designs
- Research and evaluate new models’, frameworks and tools
- Document architecture experiments and decisions clearly
- Research and recommend innovative, and where possible automated approaches for system administration tasks. Identify approaches that leverage our resources and provide economies of scale
- Repair and recover from hardware or software failures. Coordinate and communicate with impacted constituencies
- Perform periodic performance reporting to support capacity planning
- Analyzing system logs and identifying potential issues with computer systems
- Performing routine audit of systems and software
Competencies
- Familiar with Python, SQL, ETL Pipeline, PyTorch, TensorFlow, Lama index and LangGraph
- Problem solving and analytic skills
- Ability to stay up to date on new systems and AI technologies
- Ability to work independently and be able to adjust to changing environments quickly
- Experience working in a 24/7 uptime environment
- Ability to train other staff
- Ability to maintain documentation on all systems related to AI
- Ability to work various small teams in and outside the IT department with shared responsibility
- Team Player
- Motivated and detail oriented
- Ability to work with limited direction and minimal oversight
Required Education
Minimum education requirement of a High School Degree or equivalent with relevant experience or a Bachelor’s degree in a related field required.
Work Environment
This job operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.
Physical Demands: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.
- Must be able to lift 25 pounds
- While performing the duties of this job, the employee is regularly required to talk and/or hear. The employee is frequently required to sit; stand; walk; use hands to finger, handle or feel; and reach with hands and arms.
Travel
Travel is not required for this position.
Other Duties
Note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.
Benefits
Tempus Unlimited offers great benefits that foster a happy fulfilling human work experience. We also have an array of growth opportunities for our employees to develop your career and enhance your experience.
- Sign on bonus
- Work/Life Balance
- Paid time off - 25 days per year for full time staff
- 14 paid Holidays
- Tempus Wellness - Medical, Dental, Dependent Care Reimbursement, FSA and HSA
- Basic Life, Short Term and Long-Term Disability
- On-site gym (Stoughton Location) and wellness initiatives
- Annual Reviews with merit-based increases
- Employee Recognition Program
- Financial Wellness - 403(b) Retirement Plan with matching
- Continuing Education, Training and Advancement opportunities
Work Authorization/Security Clearance
All offers of employment made by Tempus Unlimited are contingent upon satisfactory background check results. Pre-employment background checks will be conducted on all candidates that are offered a position at the agency in compliance with program policy as well as state and federal regulations. From time to time, these checks may be conducted on current employees to ensure compliance with all state and federal regulations and contracts.
EEO Statement
Equal Employment Opportunity is a fundamental principle at Tempus Unlimited, Inc. where employment from recruiting through the end of employment is based upon professional capabilities and qualifications without discrimination because of race, color, religion, sex, age, sexual orientation, veteran status, national origin, disability or any other characteristic as established by law. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential job functions.
Salary Context
This $100K-$140K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Tempus Unlimited, 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. This role's midpoint ($120K) sits 43% below the category median. Disclosed range: $100K to $140K.
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.
Tempus Unlimited AI Hiring
Tempus Unlimited has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Stoughton, MA, US. Compensation range: $140K - $140K.
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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