Interested in this AI/ML Engineer role at EnerSys?
Apply Now →Skills & Technologies
About This Role
Job Title: Senior Finance AI \& Automation Developer
============================================================
Requisition ID: 13329
Location:
Anytown, PA, US, 19605 Anytown, DC, US, 20001 Anytown, IL, US, 60446 Anytown, VT, US, 05001 Anytown, SD, US, 57001 Anytown, NE, US, 68104 Anytown, NV, US, 89012 Anytown, DE, US, 19707 Anytown, CT, US, 06101 Anytown, AR, US, 71630 Anytown, IA, US, 50001 Anytown, PA, US, 19610 Anytown, LA, US, 70032 Anytown, TN, US, 37363 Anytown, IN, US, 46001 Anytown, TX, US, 75006 Anytown, RI, US, 02801 Anytown, MT, US, 59001 Anytown, AZ, US, 85001 Anytown, MI, US, 48377 Anytown, MN, US, 55177 Anytown, NY, US, 13057 Anytown, FL, US, 33805 AnyTown, WA, US, 98225 Anytown, NJ, US, 07005 Anytown, MO, US, 64120 Anytown, MD, US, 21061 Anytown, GA, US, 30093 Anytown, KS, US, 64030 Anytown, WI, US, 53001 Anytown, WA, US, 98390 Anyown, UT, US, 84123 Anytown, NC, US, 27609 Anytown, ND, US, 58001 Anytown, WY, US, 82001 Anytown, OH, US, 43127 Anytown, OK, US, 73008 Anytown, NH, US, 03031 Anytown, NM, US, 87102 Anytown, MS, US, 38601 Anytown, WV, US, 24701 Anytown, KY, US, 40018 Anytown, AL, US, 35005 Anytown, CA, US, 91710 Anytown, MA, US, 01001 Anytown, ME, US, 04098 Anytown, SC, US, 29154 Anytown, ID, US, 83816 Anytown, OR, US, 97202 Anytown, CO, US, 80503 Anytown, VA, US, 20120
Home\-based Position: Yes
Regular/Temporary: Regular
Job Type: Full\-Time
Job Description:
EnerSys is a global leader in stored energy solutions for industrial applications. We have over thirty manufacturing and assembly plants worldwide servicing over 10,000 customers in more than 100 countries. Worldwide headquarters are located in Reading, PA, USA with regional headquarters in Europe and Asia. We complement our extensive line of Motive Power and Energy Systems with a full range of integrated services and systems. With sales and service locations throughout the world, and over 100 years of battery experience, EnerSys is the power/full solution for stored DC power products.
What We’re Offering
- Paid time off plus paid holidays
- Medical/dental/vision insurance plan
- Life insurance, short/long term disability, tuition reimbursement, flex spending, and employee stock purchase plan
- 401K plan
- Culture: We value and strive for excellence in all that we do through innovative technology by creating long lasting relationships with our stakeholders, co\-workers, and customers. We continually strive to foster teamwork, engagement and enhance our employee’s skills and competence by providing appropriate training.
Compensation Range: $95,300\.00 \- $119,100\.00
Compensation may vary based on applicant's work experience, education level, skill set, and/or location.
Work Arrangement: Hybrid (Reading, PA) or Remote
Hybrid Schedule for Local Candidates:
- Monday \& Friday: Remote
- Tuesday–Thursday: Onsite at our Reading, PA location
Candidates outside the Reading, PA area may be considered for a fully remote arrangement.
Job Purpose
---------------
The Senior Finance AI \& Automation Developer’s primary responsibilities are to design, build, \& deploy automation and AI\-driven solutions across Finance processes. These projects will require project leadership and coordination with cross\-functional departments. This role sits at the intersection of Finance, Technology, and Process Improvement and focuses on eliminating manual work, accelerating reporting cycles, and enabling scalable, intelligent workflows across the Finance organization. The role will partner with finance teams to map current processes, identify automation opportunities, and redesign workflows to reduce manual effort and cycle time. This position will deploy solutions into production environments, validate outputs with stakeholders and coordinate with IT for access, infrastructure, \& governance. The position will also monitor performance of automations \& AI solutions as well as identify additional use cases and scale successful pilots. Responsibilities may also include other adhoc tasks such as Value Stream analysis and Finance SharePoint Administration, etc.
Essential Duties and Responsibilities
-----------------------------------------
- Design and Build Automation Solutions
- Transformation Project Leadership
- Power BI, Power Automate, \& Power Query Projects
- AI Agent \& Chatbot Projects
- AI Workflow Projects
- Predictive Modeling Projects
- Educate Finance Team about AI Applications \& Tools
- Project Documentation and Change Management
- Finance SharePoint Site Administration
- Ad Hoc Projects \& Tasks
SUPERVISORY RESPONSIBILITIES: No direct reports but will lead projects
Qualifications
------------------
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education and/or Experience:
- Bachelors’ degree in Engineering, Technology field, and/or Finance or equivalent
- Project Management experience required
- Digital Process Automation experience required
- AI workflow experience required
- AI Agent creation experience required
- App building experience required (personal and/or professional)
- AI\-generated coding experience required (i.e. Claude Code, Codex)
- Azure experience required
- Strong understanding of data structure and APIs required
- Experience with Python and/or other code languages required
- 6 Sigma Black Belt certification preferred
- Lean methodology experience preferred
- Strong IT skills including proficiency with Microsoft Office applications; enterprise resource planning systems (i.e., SAP), etc.
- Power BI, Power Automate, \& Power Query experience preferred
- 3\-5 Years of relevant experience or equivalent based on project volume and scope
Other Skills:
- Creative in finding solutions and overcoming obstacles
- Initiative: Aggressive while using good judgment
- Skilled with data management \& project completion
- Ability to present findings and data to different audiences up to the Executive level
- Team player while also excelling as an individual contributor.
- Fast learner with strong analytical and problem\-solving skills.
- Able to successfully manage multiple projects and tasks with various deadlines.
- Articulate, Positive \& Outgoing communicator
- Optimistic change agent that stays on the cutting edge of technology and technical requirements.
- Curious: willing to ask questions and learn
- Highly motivated
- Adaptable to change
- Exhibit a servant attitude toward colleagues and internal customers
General Job Requirements
----------------------------
- This position will work in an office setting, expect minimal physical demands.
EnerSys provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Know Your Rights
Know Your Rights (Spanish)
We use artificial intelligence to screen, assess and select applicants for open positions, including for the purposes of reviewing and ranking application materials and scoring answers to application questions. Accordingly, decisions about your application and eligibility for employment with EnerSys may be made based exclusively on the automated processing of the personal information that you submit in your application materials.
Nearest Major Market: Reading PA
Salary Context
This $95K-$119K 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 EnerSys, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($107K) sits 50% below the category median. Disclosed range: $95K to $119K.
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.
EnerSys AI Hiring
EnerSys has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Reading, PA, US. Compensation range: $119K - $119K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.