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About This Role
Director of SOLVE Sustainability
Location: Remote \- US
We're looking for a motivated Director of Sustainability to take ownership of our SOLVE sustainability programs. This role is ideal for a driven, data\-oriented individual who thrives in a fast\-paced environment and wants to directly influence revenue growth through strategic, measurable sales campaigns and relationship development.
You will be responsible for managing and optimizing our SOLVE Sustainability programs, developing new business partnerships, generating high\-quality relationships, driving sales opportunities and managing the data from our farm leaders engaged in these programs.
This is a performance\-based role with a base salary and a bonus commission structure tied to qualified sales opportunities generated from your efforts.
The Company
Agrellus provides the most comprehensive solutions for ag input procurement through the Agrellus Marketplace, farm scale crop trials through Agrellus Proving Ground, and sustainability program execution through Agrellus SOLVE. By connecting the world to the acre through Agrellus’ innovative solutions, we drive revenue back to the farm \- We Pay Farmers!
At Agrellus, we are driven by purpose, rooted in integrity, and united by innovation. Our culture thrives on collaboration, agility, and a relentless commitment to empowering American agriculture. We foster an environment where every voice is valued, creativity is encouraged, and results are recognized. As a fast\- growing ag\-tech company, we believe in blending cutting\-edge technology with real\-world farming insight—transforming the way the ag industry sources and supplies essential products. Join us and be part of a mission\-focused team that values trust, transparency, and making a measurable impact in the lives of growers and suppliers across the country.
Key Responsibilities include but are not limited to:
- Expand, grow, and innovate the SOLVE revenue line within the Agrellus universe.
- Independently identify, manage, and resolve issues related to CI calculations and data integrity.
- Develop and implement process improvements for data collection, reporting, and compliance support.
- Daily focus towards connecting with SAF users, ethanol plants, CPGs’, CI End Buyers, and Growers who can benefit from leveraging our programs, etc..
- Managing a consistent flow of VIP relationships to extend the value of the SOLVE programs to the sustainability markets.
- Managing the "SOLVE" platform to connect precise acre metrics to Enterprise sustainability initiatives.
- Develop, manage, and implement process improvements for data collection, reporting, and compliance support.
- Address and resolve day\-to\-day program and data management challenges.
- Collaborate with cross\-functional Agrellus Account Managers to identify and prioritize carbon reduction opportunities.
Qualifications:
- Bachelor’s degree in environmental science, sustainability, engineering, business, information technology or related field (master’s preferred).
- 5\+ years of experience in sustainability or compliance program management, data analysis, or regulated fuel pathways.
- Experience with CI calculations, Low Carbon Fuel Standards, “LCFS”, Scope\-3, 45Z, SAF, Carbon inset and offset programs.
- Strong project management, analytical, and communication skills.
- Strong understanding of sales and marketing, relationship development, funnel strategy, and lead generation.
- Experience working in CRM’s such as HubSpot and Salesforce.
- Excellent analytical skills and experience with KPI performance tracking.
- Highly organized with the ability to manage multiple projects and timelines.
- Experience working in a disciplined fast\-growing company environment is a plus.
What We Offer:
- Competitive base salary \+ bonuses on closed revenue transactions
- A fast\-paced, collaborative, and supportive work environment.
- Opportunity to directly impact company growth and strategy.
- Access to the latest tools and resources.
- Flexible PTO.
Compensation Structure:
Base Salary with Bonuses: $90,000\-$160,000
Pay: $90,000\.00 \- $100,000\.00 per year
Benefits:
- Paid time off
Work Location: Remote
Salary Context
This $90K-$100K range is below the median 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 Agrellus, 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. Director-level AI roles across all categories have a median of $244,288. This role's midpoint ($95K) sits 43% below the category median. Disclosed range: $90K to $100K.
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.
Agrellus AI Hiring
Agrellus has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $100K - $100K.
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
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