Interested in this AI/ML Engineer role at Alight Solutions?
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About This Role
Our Story
At Alight, we believe a company’s success starts with its people. Alight embraces values that come directly from our people – purposeful, human, united and growth\-minded – reflecting our inclusive culture and promise that our clients expect. We are passionate about connecting purpose with impact. Alight empowers clients to build a healthier and more financially secure workforce by unifying the benefits ecosystem across health, wealth, wellbeing, navigation, and absence management.
Our Benefits
With a comprehensive total rewards package, Alight offers programs and plans that support your mind, body, wallet, and life. Benefits include health, dental and vision coverages starting Day One. Additionally, Alight colleagues enjoy wellbeing programs, retirement plans with contribution matching, generous time off, parental leave, continuing education, and career growth opportunities – all within a thriving global organization.
Flexible Working
So that you can be your best at work and home, we consider flexible working arrangements wherever possible. Alight has been a leader in the flexible workspace and “Top 100 Company for Remote Jobs” 6 years in a row.
Great Place to Work
Thanks to the work of every colleague, Alight has received multiple awards of recognition including “Great Place to Work” for the past 7 years and Fortune’s “Best Companies to Work For.” To learn more about our company culture and awards Click Here.
We invite you to join our team! Learn more at careers.alight.com.
We are currently seeking an experienced AI engineer who will collaborate closely with cross\-functional teams to develop and deploy AI\-powered features and tools that optimize employee experiences and drive business outcomes.
Key Responsibilities
- As a senior AI/ML engineer, you will be responsible for designing, developing, and deploying machine learning models and AI applications that solve complex business problems.
- Design and develop search and chat applications that utilize agentic AI.
- Design and develop AI pathed paths for the Alight engineering organization.
- Experiment to evaluate application performance, including designing experiments to evaluate the performance of machine learning models, and then analyze and interpret the results to improve model performance.
- Stay up to date with new tools and technologies and evaluating their potential impact on the business.
- Work with stakeholders to develop and tune algorithms to address business needs. You should be able to effectively communicate your ideas in non\-technical terms to help educate business partners
- Collaborate on a high\-performing, agile team with a global presence
Requirements
- Bachelor’s degree with preferred concentrations in Computer Science, Data Science, Math, Actuarial Science, Engineering, or related field.
- Experience writing and working in Python or Spark (ScalaSpark or PySpark) and with popular machine learning libraries such as TensorFlow, Keras, PyTorch
- AI/ML engineers should have experience with data preparation and data engineering tasks such as data cleaning, feature engineering, and data transformation
- Knowledge of deep learning architectures and techniques, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and reinforcement learning.
- Familiarity with AWS data and data science tools including SageMaker, Glue, Lambdas, etc.
- Experience in Agile and DevOps development process
- Must be able to clearly communicate complex technical concepts to a non\-technical audience
- Manage services provided to the federal government or federal government contractor and therefore requires US Citizenship. Proof of citizenship status will be required at time of hire.
- Familiarity with Git, JIRA, Artifactory, CI/CD tools like Jenkins
Application and Interview
By applying for a position with Alight, you understand that, should you be made an offer, it will be contingent on your undergoing and successfully completing a background check consistent with Alight’s employment policies. Background checks may include some or all the following based on the nature of the position: SSN/SIN validation, education verification, employment verification, and criminal check, search against global sanctions and government watch lists, credit check, and/or drug test. You will be notified during the hiring process which checks are required by the position.
Alight requires all virtual interviews to be conducted on video. Please be aware that Alight is a camera\-on culture and may require occasional travel to one of our physical office locations.
Our commitment to Inclusion
We celebrate differences and believe in fostering an environment where everyone feels valued, respected, and supported. We know that diverse teams are stronger, more innovative, and more successful.
At Alight, we welcome and embrace all individuals, regardless of their background, and are dedicated to creating a culture that enables every employee to thrive. Join us in building a brighter, more inclusive future.
As part of this commitment, Alight will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact [email protected].
Equal Opportunity Policy Statement
Alight is an Equal Employment Opportunity employer and does not discriminate against anyone based on sex, race, color, religion, creed, national origin, ancestry, age, physical or mental disability, medical condition, pregnancy, marital or domestic partner status, citizenship, military or veteran status, sexual orientation, gender, gender identity or expression, genetic information, or any other legally protected characteristics or conduct covered by federal, state, or local law. In addition, we take affirmative action to employ disabled persons, disabled veterans, and other covered veterans.
Alight provides reasonable accommodations to the known limitations of otherwise qualified employees and applicants for employment with disabilities and sincerely held religious beliefs, practices and observances, unless doing so would result in undue hardship. Applicants for employment may request reasonable accommodations/modifications by contacting their recruiter.
Authorization to work in the Employing Country
Applicants for employment in the country in which they are applying (Employing Country) must have work authorization that does not, now or in the future, require sponsorship of a visa for employment authorization in the Employing Country and with Alight.
Note, this job description does not restrict management's right to assign or reassign duties and responsibilities of this job to other entities; including but not limited to subsidiaries, partners, or purchasers of Alight business units.
\#Li\-Remote
P\&T2026
We offer you a competitive total rewards package, continuing education \& training, and tremendous potential with a growing worldwide organization.
Salary Pay Range
Minimum :
120,000\.00 USD
Maximum :
160,000\.00 USD
Pay Transparency Statement: Alight considers a variety of factors in determining whether to extend an offer of employment and in setting the appropriate compensation level, including, but not limited to, a candidate’s experience, education, certification/credentials, market data, internal equity, and geography. Alight makes these decisions on an individualized, non\-discriminatory basis. Bonus and/or incentive eligibility are determined by role and level. Alight also offers a comprehensive benefits package; for specific details on our benefits package, please visit: Wellbeing and Benefits Selector Page \- Alight
DISCLAIMER:
Nothing in this job description restricts management's right to assign or reassign duties and responsibilities of this job to other entities; including but not limited to subsidiaries, partners, or purchasers of Alight business units.
Alight Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, creed, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, pregnancy, childbirth or related medical condition, veteran, marital, parental, citizenship, or domestic partner status, or any other status protected by applicable national, federal, state or local law. Alight Solutions is committed to a diverse workforce and is an affirmative action employer.
Salary Context
This $120K-$160K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Alight Solutions, 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($140K) sits 36% below the category median. Disclosed range: $120K to $160K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Alight Solutions AI Hiring
Alight Solutions has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in IL, US. Compensation range: $160K - $160K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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