Interested in this AI/ML Engineer role at Navtech?
Apply Now →About This Role
We're a Gartner\-recognized AI services company helping enterprises put GenAI into production through domain\-specific language models, agentic AI, and Intelligence Engineering. Media \& Entertainment is one of our fastest\-growing verticals, and we're looking for our first dedicated Senior Account Executive in LA to own it.
If you understand how studios, streamers, production and post\-production houses, gaming companies, and media networks buy enterprise technology—and you can sell complex, consultative AI services from first conversation through signed engagement—this is a rare opportunity to build a high\-impact business in one of the fastest\-growing AI markets.
Compensation:
$150,000 \- $200,000 yearly
Responsibilities:The role
You'll own the full sales cycle for Media \& Entertainment clients across LA, turning inbound opportunities and self\-generated pipeline into signed GenAI implementation engagements. This is a consultative, multi\-stakeholder enterprise sale—you'll qualify opportunities, shape solutions with our engineering teams, lead commercial discussions, navigate procurement, security, legal, and executive stakeholders, close deals, and ensure a seamless transition to our delivery and account management teams.
Working as a Senior Account Executive at Navtech, you will:
- Own opportunities from first call through contracting — discovery, solutioning, proposals, security reviews, negotiations, and close.
- Qualify opportunities rigorously and make sharp go / no\-go decisions.
- Build pipeline from both inbound leads and your own Media \& Entertainment network.
- Lead responses to RFPs, RFIs, and enterprise procurement processes.
- Orchestrate cross\-functional teams — engineering, delivery, legal, finance, and security — while aligning client stakeholders throughout the sales cycle.
- Build trusted relationships with business and technology leaders, including executive stakeholders.
- Onboard new customers and transition them smoothly to Delivery and Account Management.
Qualifications:Who Are We Looking For Exactly?
- 8\+ years closing complex, consultative B2B deals — ideally in AI services, IT services, enterprise software, cloud, or systems integration.
- Experience selling into Media \& Entertainment organizations, with a network you can leverage across studios, streaming platforms, production or post\-production companies, gaming, or media networks.
- The ability to sell technical, AI\-led engagements credibly — you can articulate business value and ROI without being an engineer, and know when to bring one into the conversation.
- A track record navigating multi\-stakeholder enterprise deals through procurement, IT, security, legal, and executive stakeholders.
- Strong discovery skills and a structured qualification approach (MEDDICC, MEDDIC, BANT, or similar).
- A self\-starter who thrives with autonomy and can work across time zones with a global delivery team.
Bonus points: Experience selling GenAI, AI/ML, cloud, or data services; relationships with studios, streamers, broadcasters, production or post\-production companies, gaming organizations, or media networks; familiarity with content operations, localization, media asset management (MAM), digital asset management (DAM), audience analytics, advertising technology, or content supply chain workflows.
About Company
Navtech is a premier IT software and Services provider. Navtech’s mission is to increase public cloud adoption and build cloud\-first solutions that become trendsetting platforms of the future. We have been recognized as the Best Cloud Service Provider at GoodFirms for ensuring good results with quality services.
Here, we strive to innovate and push technology and service boundaries to provide best\-in\-class technology solutions to our clients at scale. We deliver to our clients globally from our state\-of\-the\-art design and development centers in the US, Hyderabad, and Pune. We’re a fast\-growing company with clients in the United States, UK and Europe.
Why Navtech?
- Yearly performance review and Appraisals.
- Competitive pay package with additional bonus and benefits.
- Work with US, UK and Europe based industry\-renowned clients for exponential technical growth.
- Opportunities to work on multiple projects.
- Work with a culturally diverse team from different geographies.
Salary Context
This $150K-$200K range is above the median 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 Navtech, 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 $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($175K) sits 19% below the category median. Disclosed range: $150K to $200K.
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.
Navtech AI Hiring
Navtech has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $200K - $200K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% 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 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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