Interested in this AI/ML Engineer role at Neurocrine Biosciences?
Apply Now →Skills & Technologies
About This Role
Who We Are:
At Neurocrine Biosciences, we pride ourselves on having a strong, inclusive, and positive culture based on our shared purpose and values. We know what it takes to be great, and we are as passionate about our people as we are about our purpose \- to relieve suffering for people with great needs.
What We Do:
Neurocrine Biosciences is a leading neuroscience\-focused, biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering and developing life\-changing treatments for patients with under\-addressed neurological, neuroendocrine and neuropsychiatric disorders. The company's diverse portfolio includes FDA\-approved treatments for tardive dyskinesia, chorea associated with Huntington's disease, classic congenital adrenal hyperplasia, endometriosis\* and uterine fibroids,\* as well as a robust pipeline including multiple compounds in mid\- to late\-phase clinical development across our core therapeutic areas. For three decades, we have applied our unique insight into neuroscience and the interconnections between brain and body systems to treat complex conditions. We relentlessly pursue medicines to ease the burden of debilitating diseases and disorders because you deserve brave science. For more information, visit neurocrine.com, and follow the company on LinkedIn, X and Facebook. (*\*in collaboration with AbbVie*)
About the Role:
Interacts with scientific leaders and healthcare decision makers to communicate and advance the scientific platform for therapeutic areas that are aligned with the Neurocrine corporate strategy. Supports company sponsored and investigator\-initiated research, deliver clinical and pharmacoeconomic presentations to payers, train faculty for the speaker’s bureau, support scientific congresses, and be a resource for medical and scientific inquires. May also represent the company at identified patient advocacy, professional society, or other meetings. This territory covers VA, NC and SC, the ideal candidate will live within this geography and close to a major airport.
\_
Your Contributions (include, but are not limited to):* Establishes peer\-to\-peer, science\-based relationships with KOLs and healthcare decision makers
- Serve as a scientific resource for scientific leaders and internal personnel
- Delivers fair, balanced, and credible medical and scientific presentations
- Supports company\-sponsored and investigator\-initiated research
- Participates in conferences and meetings as a scientific expert on the Company’s behalf
- Trains faculty on scientific content for the company’s speaker’s bureau
- Obtains clinical insights to help strategically guide the educational efforts of the organization
- Performs responsibilities with the highest ethical standards including FDA guidelines, healthcare compliance/SOPs and best practices for the pharmaceutical industry
- Other duties as assigned
Requirements:* PhD, PharmD or equivalent AND 2\+ years of previous work experience in an equivalent field\-based position is required. Psychiatry or neurology experience preferred OR
- MD AND Some relevant experience
- Has knowledge of best practices in the functional discipline and familiarity with the broader underlying concepts of related business disciplines
- Works to improve tools and processes within functional area
- Developing reputation inside the company as it relates to area of expertise
- Ability to work as part of and lead multiple teams
- Exhibits leadership skill and ability, may lead lower levels and/or indirect teams
- Excellent computer skills
- Excellent problem\-solving, analytical thinking skills
- Sees broader picture, impact on multiple departments/divisions
- Ability to meet multiple deadlines across a variety of projects/programs, with a high degree of accuracy and efficiency
- Excellent organizational and project management skills
- Excellent oral, written and presentation skills
- Ability to work cross\-functionally is essential
- Must be a strong communicator and skilled diplomat in all venues, including the ability to effectively combine scientific knowledge and communication skills
- Strong territory management and execution of scientific leader communication plans
- Demonstrated ability to develop strong business relationships with healthcare professionals, key decision makers, and other external and internal collaborators is required
- Proven ability to meet individual goals, enhance therapeutic knowledge and continuously improve knowledge, skills and abilities related to job expectations
- Good understanding of drug development and life\-cycle management of a product is preferred
- Working knowledge of healthcare compliance requirements and regulatory trends that directly and indirectly impact field medical
\#LI\-SA1
Neurocrine Biosciences is an EEO/Disability/Vets employer.
We are committed to building a workplace of belonging, respect, and empowerment, and we recognize there are a variety of ways to meet our requirements. We are looking for the best candidate for the job and encourage you to apply even if your experience or qualifications don’t line up to exactly what we have outlined in the job description.
\_
The annual base salary we reasonably expect to pay is $160,900\.00\-$220,000\.00\. Individual pay decisions depend on various factors, such as primary work location, complexity and responsibility of role, job duties/requirements, and relevant experience and skills. In addition, this position offers an annual bonus with a target of 30% of the earned base salary and eligibility to participate in our equity based long term incentive program. Benefits offered include a retirement savings plan (with company match), paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage in accordance with the terms and conditions of the applicable plans.
Salary Context
This $160K-$220K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Neurocrine Biosciences, 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 $166,983 based on 13,781 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($190K) sits 14% above the category median. Disclosed range: $160K to $220K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Neurocrine Biosciences AI Hiring
Neurocrine Biosciences has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $168K - $220K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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.