Interested in this AI/ML Engineer role at Sinclair Broadcast Group?
Apply Now →Skills & Technologies
About This Role
Tennis Channel is seeking a driven and business-oriented Corporate Counsel, Business & Legal Affairs with 3–5 years of post–law school experience to join our in-house Legal Department. This role is ideal for someone who thrives where media, sports, creativity, and business intersect and is excited to continue growing their in-house career while supporting Tennis Channel's expansion. The attorney in this role will support a wide range of legal matters, including content rights and licensing, commercial contracting, intellectual property, and cross-functional advisory work. This role reports to the General Counsel, SVP of Business Affairs.
This is a unique opportunity for a mid-level attorney to gain broad exposure in a fast-paced sports media environment, taking on diverse legal issues while learning new domains. You'll work closely with production, digital, marketing, operations, technology, and corporate teams, translating legal concepts into clear, actionable advice for non-legal partners to help enable the business while managing legal risk.
This role is onsite and based in Santa Monica, CA office.
In this role, you will :
*Support Content Rights, Licensing & Media Clearance*
- Work closely with internal stakeholders on content rights renewals and new rights opportunities with the ATP, WTA, the Grand Slams, and others.
- Evaluate rights restrictions tied to sports leagues, tournaments, and talent.
- Review production materials and marketing assets for rights compliance and risk mitigation.
- Advise internal stakeholders on the acquisition and use of music, footage, images, player likeness, graphics, and other media assets across broadcast, digital, and social platforms.
- Draft and negotiate content licenses, appearance releases, location releases, clip licenses, and image rights agreements.
*Draft, Review & Negotiate Commercial Contracts*
- Draft, review, and negotiate a wide variety of commercial contracts, including talent agreements, licensing deals, service agreements, technology contracts, sponsorship/marketing agreements, and NDAs.
*Provide Corporate, Compliance & Governance Support*
- Develop, refine, and implement internal policies, procedures, forms, and templates to support business operations.
*Manage Intellectual Property Matters*
- Support and manage trademark, copyright, and domain name portfolios.
- Advise internal teams on IP strategy, usage guidelines, and brand protection efforts.
*Partner on Cross-Functional Advisory Responsibilities*
- Serve as a trusted legal advisor to departments, including operations, HR, marketing, production, digital, and finance.
- Collaborate with internal teams to develop strategies for addressing legal issues and improving workflows.
- Provide training and practical legal insights to internal teams.
*Provide General In-House Legal Support*
- Assist senior attorneys with complex transactions, strategic initiatives, and special projects.
- Handle miscellaneous legal matters as they arise.
Qualifications:
- J.D. from an ABA accredited law school; membership in good standing in a US State Bar
- At least 3–5 years of legal experience at a law firm and/or in-house
- Strong foundation in contract drafting and negotiation
- Familiarity with intellectual property, licensing, privacy, and media law
- Business-minded approach with strong risk-balancing judgment
- Excellent communication, negotiation, and organizational skills
- Ability to work independently and collaboratively in a fast-paced environment
- Strong research, writing, and analytical skills with exceptional attention to detail
- Proactive communicator with strong interpersonal skills and a team-first mindset
- Desire to contribute to broader company growth and operational improvements
- Hands-on, pragmatic approach to problem-solving and project management
Experience in sports, media, entertainment, and live events is a plus
Tennis Channel is proud to be equal opportunity employer and a drug free workplace. Employment practices will not be influenced or affected by virtue of an applicant's or employee's race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, military or veteran status or any other characteristic protected by law.
About PickleballTV
Pickleballtv (PBTV) is the 24-hour television home of America's fastest growing sport. With coverage of tournaments throughout the year, the network offers 1,000 plus hours of live matches from the game's top professionals and biggest stars. PBTV also provides viewers with first-class instruction, exclusive lifestyle programming and studio news content and more.
About Tennis Channel
Tennis Channel is the media home to two twenty-four-hour television networks, a subscription streaming service, online magazine and podcasts dedicated to the sport and its unique lifestyle. The tennis-media hub is home to every aspect of the wide-ranging, worldwide tennis community. Tennis Channel is carried nationwide by every one of the top ten pay-TV service providers.
About Sinclair
Sinclair, Inc. (Nasdaq: SBGI) is a diversified media company and a leading provider of local news and sports. The Company owns, operates and/or provides services to 178 television stations in 81 markets affiliated with all major broadcast networks; owns Tennis Channel, the premium destination for tennis enthusiasts; multicast networks CHARGE, Comet, ROAR and The Nest. Sinclair's AMP Media produces a growing portfolio of digital content and original podcasts. Additional information about Sinclair can be found at  www.sbgi.net .
About the Team
The life-blood of our organization is our people. We have a compelling story, a goal-oriented culture, and we take really good care of people. How good? Here is a glimpse: great benefits, open-door policy, upward mobility and a strong desire to see you succeed. Ready to be part of a winning team? Let's talk.
The base salary compensation range for this role is $120,650 to $134,062. Final compensation for this role will be determined by various factors such as a candidates' relevant work experience, skills, certifications, and geographic location. Full time positions are eligible for benefits that include participation in a retirement plan, life and disability insurance, health, dental and vision plans, flexible spending accounts, sick leave, vacation time, personal time, parental leave and employee stock purchase plan.
#tennis
Salary Context
This $120K-$134K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Sinclair Broadcast Group, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($127K) sits 17% below the category median. Disclosed range: $120K to $134K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Sinclair Broadcast Group AI Hiring
Sinclair Broadcast Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Santa Monica, CA, US. Compensation range: $134K - $134K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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.