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About This Role
Looking to join a passionate team dedicated to developing and manufacturing life\-saving biopharmaceuticals? Avid Bioservices is a leading clinical and commercial biologics CDMO focused on creating innovative solutions to meet the needs of our clients and improve patient outcomes.
Your Role:
The AI Engineer is a developing professional role responsible for supporting the design, development, testing, deployment, and ongoing support of artificial intelligence, automation, and data\-enabled business solutions across Avid Bioservices. This role partners with business stakeholders and technical teams to understand current workflows, identify practical opportunities for improvement, and implement AI\-enabled solutions that improve efficiency, quality, documentation, and employee productivity.
Key Responsibilities:
- Design, develop, test, deploy, and support AI\-enabled applications, automations, workflows, and business solutions using approved enterprise platforms and technologies.
- Assist with proof\-of\-concept, pilot, and enhancement activities for solutions involving large language models, AI agents, workflow automation, OCR, document intelligence, and related technologies.
- Collaborate with business stakeholders to understand current\-state processes, pain points, operational requirements, and opportunities for process improvement.
- Translate business requirements into technical designs, functional configurations, workflow diagrams, and implementation documentation.
- Troubleshoot and resolve issues related to AI\-enabled solutions, integrations, automations, and user adoption.
- Support AI governance, security, privacy, validation, change control, and documentation expectations in partnership with IT, Quality, and business stakeholders.
- Maintain solution documentation, including design decisions, requirements, workflows, configurations, test results, deployment notes, and support procedures.
- Measure and communicate practical outcomes such as cycle\-time reduction, productivity gains, quality improvements, and user adoption for assigned projects.
- Stay current on artificial intelligence, automation, Microsoft technologies, and relevant enterprise technology trends.
- Other duties as assigned.
Minimum Qualifications:
- Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, Artificial Intelligence, or a related technical discipline with 2 or more years of relevant experience; or a master's degree/PhD in a related discipline with no prior professional experience.
- Experience developing or supporting solutions using programming languages such as Python, JavaScript, C\#, or similar.
- Foundational understanding of APIs, structured and unstructured data, systems integration, workflow automation, and software development concepts.
- Foundational understanding of artificial intelligence, machine learning, large language models, prompt engineering, AI agents, or automation technologies.
- Strong analytical, troubleshooting, documentation, and problem\-solving skills.
- Strong written, verbal, and interpersonal communication skills, with the ability to work effectively with technical and non\-technical stakeholders.
- Ability to manage multiple priorities, follow established standards, and work independently within an established framework.
- Demonstrated curiosity, initiative, and willingness to learn emerging technologies.
Preferred Qualifications:
- Experience with Microsoft Copilot Studio, Microsoft 365 Copilot, Power Platform, AI Builder, Azure AI Services, or related Microsoft technologies.
- Experience with workflow automation platforms, low\-code/no\-code development environments, or business process automation tools.
- Familiarity with OCR, document intelligence, knowledge management, retrieval\-augmented generation, AI agent development, or prompt engineering.
- Knowledge of SQL, Power BI, data visualization, reporting, or data analysis tools.
- Experience developing prototypes, proof\-of\-concepts, or internal business tools.
- Experience working in regulated industries such as biotechnology, pharmaceuticals, healthcare, life sciences, or manufacturing.
- Exposure to software development lifecycles, Agile methodologies, validation concepts, or product development practices.
Position Type/Expected Hours of Work:
This role is a full\-time onsite position. Days and hours of work are Monday through Friday 8:00 a.m. to 5:00 p.m. unless otherwise stated by Supervisor. The employee must also have the ability to work overtime and/or weekends when necessary.
Compensation:
We offer competitive compensation packages for this role, including a base salary, performance\-based bonuses, and comprehensive benefits such as health, dental, and vision insurance, 401(k) matching, and paid time off.
The compensation range for this role is $80,000 \- $100,000 annually depending on experience and qualifications. Additionally, we offer opportunities for career growth and development as well as a supportive and inclusive work environment.
Who you are:
- You have a "bring it on!" team player approach and an unshakable positive attitude, always ready to tackle anything that comes your way.
- Your written and verbal skills are out of this world, and you communicate with clarity and confidence.
- You have exceptional multitasking skills and an unparalleled attention to detail that ensure the smooth running of everything.
- You are a master at building relationships, capable of establishing connections with anyone, be it team members, clients, vendors, or suppliers.
Physical Demands \& Work Environment:
In this dynamic role, expect a blend of regular activities like sitting, standing, and walking, with occasional physically engaging tasks such as lifting objects up to 25 pounds. The work environment might expose you to electrical shocks, toxic chemicals, vibrations, or loud noise levels occasionally. However, reasonable accommodations are available to enable individuals with different abilities to perform effectively, ensuring a supportive and adaptable work setting. Your visual acuity, including close, distance, and color vision, will be essential in navigating through the diverse day\-to\-day demands of this position.
Salary Context
This $80K-$100K 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 Avid Bioservices, 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. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($90K) sits 58% below the category median. Disclosed range: $80K to $100K.
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.
Avid Bioservices AI Hiring
Avid Bioservices has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Tustin, CA, US. Compensation range: $100K - $100K.
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
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