Interested in this AI/ML Engineer role at LS Power Development, LLC?
Apply Now →Skills & Technologies
About This Role
Overview:
About us:
Founded in 1990, LS Power is a premier development, investment, and operating company focused on the North American power and energy infrastructure sector, with leading platforms across generation, transmission and energy expansion solutions. Since inception, LS Power has developed or acquired 50,000 MW of power generation, including utility\-scale solar, wind, hydro, battery energy storage, and natural gas\-fired facilities. Through its transmission business, LS Power Grid, the company built and operates 780\+ miles of high\-voltage transmission and 7 transmission utilities and has another 375\+ miles currently in construction or development. LS Power actively invests in and scales businesses that are meeting the growing needs of the energy expansion, including electric vehicle charging, demand response, microgrids, renewable fuels and waste\-to\-energy platforms. Over the years, LS Power has raised more than $76 billion in debt and equity capital to support North American infrastructure.
Our Purpose, Mission, \& Values:
Our Purpose is to solve complex energy problems that improve the world
Our Mission is to make lives better by developing a cleaner and more reliable energy ecosystem
Our Values are the willingness to participate in and help strengthen our culture of integrity, Innovation, Teamwork, and Taking Ownership
Our People create value and are our Most Valuable asset. We take our values of Integrity, Innovation, Teamwork and Taking Ownership seriously and ask candidates to think about how they can help us further enhance our culture with their specific skillsets, capabilities and experiences.
Benefits
We provide our team the opportunity to share their unique perspectives, solve new challenges, and continue in their career growth. We are committed to supporting employees’ happiness, healthiness, and overall well\-being by providing comprehensive benefits that include 100% employer paid premium healthcare, paid parental leave and more.
Compensation
The salary for this role is $90,000\-$130,000\. This is the range that we in good faith anticipate relying on when setting wages for this position. We may ultimately pay more or less than the posted range and this range is only applicable for jobs to be performed in New York. This salary range may also be modified in the future.
About the Role:
As LS Power expands its use of AI and automation across business units, we are seeking an AI \& Automation Developer to serve as an embedded technical resource within a designated business unit. In this role, you will work directly with business leadership and subject matter experts to identify opportunities, build solutions, and deploy tools that improve efficiency and decision\-making.
This is a highly hands‑on role for a pragmatic builder who can translate business processes into technical solutions, select appropriate tools or models, and develop production‑ready applications in an enterprise environment. You will operate with a high degree of ownership, functioning as a dedicated technical resource within the business unit, while collaborating with LS Power’s broader technology and development community.
Responsibilities:
What you will do:
*Build \& Deploy Automation*
- Design, develop, and maintain automation workflows and AI‑enabled tools to improve efficiency and reduce manual processes.
- Leverage large language model (LLM) APIs (e.g., OpenAI, Claude) and agentic frameworks to build task‑specific applications.
- Integrate solutions with existing enterprise systems, data sources, and SaaS platforms.
*Partner with the Business*
- Translate business needs into technical requirements and scalable solutions.
- Collaborate directly with operators, analysts, and leadership to identify high‑impact automation opportunities.
- Provide training and documentation to ensure adoption and long‑term maintainability of solutions.
*Collaborate Across LS Power*
- Coordinate with central IT on security reviews, enterprise architecture, and governance standards.
- Partner with developers across business units to share best practices, reuse components, and align on development standards.
- Contribute to the evolution of LS Power’s AI governance framework and technical ecosystem.
Qualifications:
We want you on our team because you…
- Bring hands‑on experience building and deploying automation or software solutions in an enterprise environment.
- Are proficient in Python and/or JavaScript and comfortable working across the full development lifecycle.
- Have experience working with LLM APIs, prompt engineering, and building production‑ready integrations.
- Can independently scope, build, and deploy solutions with minimal oversight.
- Communicate effectively with both technical and non‑technical stakeholders.
- Have experience working with modern development tools, including AI‑assisted coding platforms.
Ideally, you have…
- 2\+ years of professional experience in software development, automation, or related technical roles.
- Experience working with cloud\-native data platforms (e.g., Snowflake, Microsoft Fabric).
- Familiarity with unstructured data pipelines, OCR, or intelligent document processing.
- Experience with retrieval\-augmented generation (RAG) or agent\-based workflows.
- Exposure to secure software development practices and SDLC considerations.
- Experience with cloud platforms (Azure, AWS, or GCP) and enterprise security frameworks.
- Familiarity with workflow automation platforms (e.g., Power Automate).
- Prior exposure to the energy industry, power markets, or asset management environments.
Salary Context
This $90K-$130K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At LS Power Development, LLC, 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($110K) sits 39% below the category median. Disclosed range: $90K to $130K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
LS Power Development, LLC AI Hiring
LS Power Development, LLC has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $130K - $130K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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.