Interested in this AI/ML Engineer role at Patsnap?
Apply Now →About This Role
Strategic Life Sciences Data \& AI Expansion Specialist
➡️ Ready to leverage your Life Sciences expertise to influence the innovation strategies of the world's leading pharmaceutical and biotechnology organisations?
➡️ What if you could combine industry credibility, executive engagement, and cutting\-edge AI technology to help shape critical innovation, portfolio, and growth decisions?
➡️ Interested in a role where you combine the stability of a VC\-backed Unicorn with the autonomy, visibility, and influence of a role at the forefront of AI\-powered intelligence in Life Sciences?
If this sounds like your next move, we’d love to hear from you.
Role Summary:
We are seeking a highly commercial, customer\-facing Strategic Life Sciences Data \& AI Expansion Specialist to drive growth across our existing Life Sciences customer base and support high\-value strategic opportunities throughout North America.
This is an opportunity to join a business that is redefining how Life Sciences organisations discover, protect, and commercialise innovation. Trusted by leading pharmaceutical, biotech, and medical device companies worldwide, PatSnap's AI\-native platform combines patent intelligence, scientific literature, clinical trials, regulatory data, and market insights to help customers make better decisions across the innovation lifecycle.
With our Life Sciences business growing 20%\+ YoY, significant investment in AI, and ambitious expansion plans, there has never been a more exciting time to join.
The successful candidate will operate as a specialist overlay, partnering closely with Account Executives and Customer Success teams to identify, create, and accelerate expansion opportunities focused primarily on Data\-as\-a\-Service (DaaS) solutions, while also supporting broader SaaS platform opportunities where relevant.
The role requires deep Life Sciences industry expertise, exceptional executive presence, and the ability to engage credibly with R\&D, Competitive Intelligence, Business Development, Innovation, IP, and Commercial stakeholders. The successful candidate will serve as both a growth driver and industry ambassador, representing the company at conferences, customer events, executive briefings, and thought leadership engagements.
The ideal candidate combines the commercial instincts of an enterprise seller, the industry credibility of a Life Sciences expert, and the executive presence of a trusted advisor. They are equally comfortable creating expansion opportunities, influencing complex strategic deals, and representing the company as a thought leader in front of senior industry audiences.
Want to see the platform you'd be representing?
Check out this short overview:
https://www.youtube.com/watch?v\=j6fCDvnrT2g
*This is a remote US West Coast based position, ideally suited for candidates able to work flexibly across EST hours.*
Who are we?
PatSnap is a global, pre\-IPO company that transforms the way organizations harness their Intellectual Property and Research \& Development productivity. Our platform revolutionizes how IP and R\&D teams collaborate across the entire innovation lifecycle, using domain\-specific AI to accelerate the creation of market\-ready products. With over 12,000 customers worldwide, including some of the biggest names in innovation, Patsnap is at the forefront of technological advancement. Our $300M Series E funding round brings our valuation to a $1 billion unicorn status, and we still have a remarkable amount of growth ahead.
As the leading global Life Sciences intelligence platform, PatSnap helps pharmaceutical, biotech, medical device, and life sciences organisations make better innovation decisions. By connecting patents, scientific literature, clinical trials, regulatory data, and market intelligence, we enable our customers to identify white spaces, reduce R\&D risk, and accelerate breakthrough innovation.
We have a vibrant and diverse team with offices in Singapore, Toronto, London, Shanghai and remote teams based in US. Our hyper\-growth trajectory is powered by our people, and we are extremely proud of our company\-wide vision, work ethic, and entrepreneurial spirit. We are committed to fostering an inclusive environment where talent thrives and ideas bloom.
### What You'll Be Doing:
Expansion Opportunity Creation
- Develop and execute expansion strategies within existing Life Sciences customer accounts.
- Identify new use cases, business units, therapeutic areas, and stakeholder groups across pharmaceutical, biotechnology, medical device, and research organizations.
- Build relationships with senior leaders across R\&D, Portfolio Strategy, Business Development \& Licensing, Competitive Intelligence, Innovation, Corporate Strategy, and Commercial functions.
- Generate qualified expansion pipeline through executive engagement, workshops, industry events, and consultative business discussions.
- Drive adoption of data\-driven decision\-making solutions that improve innovation, competitive positioning, pipeline assessment, and market intelligence capabilities.
Strategic Deal Acceleration
- Act as a subject matter expert for Data\-as\-a\-Service opportunities across strategic Life Sciences accounts, with particular focus on complex enterprise opportunities and key West Coast deals.
- Join active sales cycles to strengthen customer engagement, shape solution strategy, and accelerate deal progression.
- Lead executive discovery sessions, value workshops, and strategic account planning activities.
- Help account teams navigate complex stakeholder environments and develop compelling business cases tied to measurable business outcomes.
- Partner with Account Executives to increase win rates, shorten sales cycles, and expand deal value.
Industry Thought Leadership
- Represent the company as a credible industry expert at Life Sciences conferences, customer forums, webinars, roundtables, and executive events.
- Deliver compelling presentations to senior customer audiences on industry trends, competitive intelligence, innovation strategy, AI, data\-driven decision making, and emerging Life Sciences market developments.
- Contribute to thought leadership content, conference speaking opportunities, and strategic customer engagement programs.
- Build a strong external presence that enhances the company’s reputation within the Life Sciences ecosystem.
Cross\-Functional Collaboration
- Operate as a strategic overlay resource supporting multiple Account Executives and territories.
- Collaborate with Product, Marketing, Customer Success, and Sales Leadership teams to drive expansion initiatives and market penetration.
- Share customer insights and market intelligence to influence product strategy and go\-to\-market execution.
- Support the development of Life Sciences\-specific messaging, sales plays, and enablement programs.
### What We'd Love From You:
- 5\+ years of enterprise sales experience within the Life Sciences sector.
- Demonstrated success selling Data\-as\-a\-Service (DaaS), scientific data, competitive intelligence, market intelligence, drug development intelligence, or related data\-driven solutions to pharmaceutical, biotechnology, or medical device organizations.
- Proven track record of expanding existing customer relationships and driving significant account growth within Life Sciences accounts.
- Deep understanding of Life Sciences industry workflows, including drug discovery, clinical development, competitive intelligence, business development \& licensing, innovation strategy, or portfolio management.
- Experience engaging and influencing VP and C\-level stakeholders.
- Exceptional communication, presentation, and executive engagement skills.
- Ability to represent the company as a credible thought leader both internally and externally.
- Willingness to travel extensively for customer meetings, conferences, executive briefings, and industry events.
Preferred Experience
- Experience selling patent intelligence, scientific intelligence, competitive intelligence, clinical intelligence, pipeline intelligence, AI\-driven research platforms, or innovation intelligence solutions.
- Existing network within pharmaceutical, biotechnology, and Life Sciences organizations.
- Experience speaking at industry conferences, customer forums, or executive events.
- Familiarity with enterprise sales methodologies such as MEDDICC, Challenger, or SPICED.
### What You'll Love:
- Unlimited vacation
- 2 volunteer days for community volunteering
- Health and dental benefits for you and your dependents from day one
- 401K matching
- Remote work environment \+ WFH stipend for your home office set\-up
- 24/7 employee assistance program which provides access to virtual healthcare, therapy, financial and legal assistance, wellness counselling and resources for family support.
### Our Values
- Integrity: We hold each other accountable for our actions.
- Leadership: We lead by example and inspire each other to reach for new heights.
- Openness: We are open and honest and share our ideas with care and consideration.
- Growth: We are lifelong learners who aspire to improve each day.
- Innovation: We seek out new ways to solve problems.
- Customer: Our customer is at the center of everything we do. Their success is our success.
$130,000 \- $260,000 a year
This position offers a 50/50 compensation structure (base salary and commission), with on\-target earnings (OTE). Commission is uncapped.
*PatSnap is proud to be an equal opportunity employer (EOE) that champions diversity. We do not discriminate based on race, religion, national origin, citizenship, sex, gender identity or expression, sexual orientation, pregnancy, age, or marital, veteran/military, or disability status, or any other protected status in accordance with federal, provincial/state or local laws.*
*Even if you don’t meet 100% of the above qualifications, we encourage you to apply and tell us why you’d be a great fit for this role! If you require any accommodations during the interview process, please email us at* *\[email protected]* *so we can best support you.*
Salary Context
This $130K-$260K range is above the median 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 Patsnap, 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 in Demand for This Role
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. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($195K) sits 8% above the category median. Disclosed range: $130K to $260K.
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.
Patsnap AI Hiring
Patsnap has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Remote, US, CA, US. Compensation range: $260K - $260K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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.