---
title: 'Senior Machine Learning Operations Engineer at AgZen'
canonical: 'https://feeny.ai/job/senior-machine-learning-operations-engineer-agzen-somerville-9jxjfy0j9v5f'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Machine Learning Operations Engineer at AgZen

- **Company:** AgZen
- **Location:** Somerville, MA
- **Employment:** full-time
- **Posted:** 2026-08-14
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/agzen/808e1e11-18ec-4df2-a263-7b1d708bbe57

## Job description

About AgZen: AgZen is a fast-growing precision agriculture company headquartered in Somerville, MA, built on MIT research and focused on one problem: making crop spraying more efficient. Our flagship product, RealCoverage, is the world's first system that measures and controls droplet coverage at the leaf level, giving growers real-time visibility into spray performance and cutting chemical and water use by up to 50% without sacrificing yield. We are a small, technically deep team working at the intersection of fluid mechanics, computer vision, AI, and real agricultural environments. If you want to build technology with measurable impact on how the world grows food, this is the place to do it.

## About the Role

We are looking for a sharp, tenacious, and thorough Senior Machine Learning Operations (MLOps) Engineer to join our team. As part of the the perception team, you’ll own the operational layer around of machine learning models. This role will be responsible for the intake and leveraging crop protection data collected from RealCoverage units installed on sprayers all around the world which is then used improve our CV pipeline and Recommendation Engine. This role will be an essential component of AgZen’s measurement focus group. Strong communication, flexibility, teamwork, the desire to take on different responsibilities and own them will all be essential skills for a successful applicant.

📍 This role is located in Somerville, MA (Boston area) with work required to be in-person.

## What You'll Do

- Own the architecture, execution, and operational excellence of large‑scale, cloud‑native pipelines for multimodal sensor data ingestion, processing, labeling, and validation.
- Champion model traceability by building a clear lineage for every production model. Track what data trained it, what code produced it, what validation it passed, and how it's performing. Evaluate and recommend tooling for versioning, metadata, and model registry
- Partner with data scientists to detect data quality issues, detect drift in upstream sources, and ensure features stay fresh and reliable
- Track model drift over weeks, flag slow degradation before it crosses a threshold, surface feature freshness problems before they cascade
- Build diagnostic tooling to root cause pipeline and recommendation issues quickly. Ensure the right context is logged at each stage, candidates, features, serving context, and building the dashboards to tie it collectively
- Own automated gates that block bad deployments and assist in running model issue retrospectives
- Work with ML engineers, data engineers, and stakeholders to coordinate on post-deployment metrics, defining what metrics to collect after deployment and why they matter
- Build tooling and support non-technical domain experts in understanding perception system performance and identifying opportunities for pipeline improvement
- Collaborate closely with cross-functional teams of software engineers, machine learning scientists, product specialists, and researchers to design, build, and maintain robust data pipelines grounded in sound data organization, domain knowledge, and careful analysis
- Communicate technical findings, data characteristics, and limitations clearly and effectively to both internal partners and external collaborators

## What We're Looking For

Required:

- Bachelor’s or graduate degree in Computer Science, Electrical Engineering, or a closely related field
- 5+ years of experience building large-scale distributed systems, applications, or advanced ML systems‑scale distributed systems, applications, or advanced ML systems
- Experience with MLOps, data pipelines, and cloud distributed systems
- Proficiency in Python for system‑level and performance‑critical implementation
- Experience operating end‑to‑end data or ML pipelines for reliability, scale, and observability
- Communication skills that align collaborators and drive execution across functions
- Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow)
- A record of ownership, accountability, and customer‑focused engineering
- Proven track record of designing robust frameworks with high-quality, durable APIs
- Deep understanding of machine learning algorithms with hands‑on application
- Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure‑performance
- Robust SQL skills and comfort digging into data distributions, feature health, and model behavior

Preferred:

- Experience with the field of agriculture or related fields such as environmental or life sciences
- Experience with data science based on real-world physical sensors data
- Experience with vision-based ML
- Experience creating intuitive data visualization tools that make complex data approachable for non-technical users
- Prior experience in developing machine-learning models relevant to biological or crop protection outcomes
- Advanced scientific Python (NumPy, Pandas, scikit-learn) and hands-on experience with PyTorch and/or TensorFlow, including training and deploying neural networks
- Experience operating recommendation systems at scale

## What We Offer

- The opportunity to make an immediate and visible impact in a fast-growing company
- Early-employee equity
- 401(k) with employer matching at 6 months of employment
- 6 weeks of PTO per calendar year
- 12 paid holidays
- Medical, Dental and Vision insurance

The salary range for this position is $150,000 - $200,000 depending on skills and qualifications evaluated on a per candidate basis.

## About AgZen

## Company Overview
- **One-liner**: AgZen develops a real-time, AI-powered smart spraying system that enables farmers to cut chemical and water use by 30‑50% while maintaining or improving crop yields.
- **Entity Type**: Private (Series B)
- **Headquarters**: Somerville, Massachusetts, United States
- **Founded**: 2022 (as a company; research roots date to 2020) [builtin.com](https://builtin.com/company/agzen)
- **Founders**: Vishnu Jayaprakash (CEO), Kripa Varanasi (Chairman, MIT Professor), Maher Damak (Co-Founder & Co-Inventor) [agzen.com](https://www.agzen.com/agzen-aboutus)

## Core Business
- **Primary industry**: Precision agriculture / AgTech
- **Target customers**: Growers (farmers), ag equipment companies, agribusinesses (e.g., Corteva, Syngenta) – primarily B2B with a direct leasing/purchase model
- **Mission**: “Empower growers with the tools to navigate agriculture’s ever-changing landscape… ensuring efficiency, profitability, and accessibility in farming’s future.” [agzen.com](https://www.agzen.com/agzen-aboutus)

## Products & Services
- **RealCoverage®**: A bolt‑on hardware + software system that uses onboard AI, computer vision, and fluid dynamics to monitor and optimize droplet coverage in real time. It adjusts speed, droplet size, boom height, and other parameters on‑the‑fly, enabling growers to use 30‑50% less chemicals and water while achieving better pest control. [agzen.com](https://www.agzen.com/agzen-whatwedo)

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric** – Total Funding: **$20M** (Series A – $10M led by DCVC Bio, April 2025; Series B – $10M led by DCVC Bio with participation from Material Impact and Astanor, 2025–2026) [agfundernews.com](https://agfundernews.com) (via search results)
- **Notable Investors/Partners**: DCVC Bio (lead), Material Impact, Astanor, Syngenta Group Ventures (strategic investment), Corteva (R&D agreement) [agzen.com](https://www.agzen.com/agzen-aboutus)
- **Growth Signals**: 
  - Acreage deployed with RealCoverage grew 15× in 2025, reaching nearly **1 million commercial acres** in the U.S.
  - For 2026, commitments exceed **2 million acres** across three continents.
  - Headcount grew **58% YoY** to **35 employees** (as of mid‑2026). [linkedin.com](https://www.linkedin.com/company/agzen)
  - Partnerships with major ag companies Corteva and Syngenta.

## Competitive Advantages
- **Real‑time feedback loop**: The only system that measures droplet coverage on every leaf while spraying, instantly adjusting parameters – a capability that has eluded the industry for decades.
- **Bolt‑on design**: Works with any existing sprayer (any generation, any brand), lowering adoption barriers.
- **Proven ROI**: Trials across 12 locations showed 30‑50% reduction in chemical use without yield loss, offering immediate payback for growers.
- **Deep IP**: Founded out of MIT, with patents covering fluid mechanics, interfacial physics, and AI‑driven spray optimization.

## Strategic Focus
- **Scale globally**: Expand from 1M acres (2025) to 2M+ acres in 2026 across North America, South America, and Europe.
- **Deepen partnerships**: Leverage agreements with Corteva and Syngenta to co‑develop and co‑market solutions.
- **Talent growth**: Continue hiring across engineering, field operations, and product management to support rapid commercial expansion.

## Why Work Here
- **Culture**: Mission‑driven team tackling agriculture’s waste and pollution problems. Multidisciplinary (engineers, ag scientists, former farmers). Small, collaborative environment with a flat structure.
- **Work setup**: On‑site at Greentown Labs in Somerville, MA (a clean‑tech incubator). Some flexibility for remote work, but most employees are expected in the office most days.
- **Perks & Benefits**:
  - Company equity grants
  - 401(k) matching
  - Generous PTO and flexible time‑off policy
  - Comprehensive health, dental, and vision insurance
  - Fast‑growing startup (35 employees, 58% YoY growth) with significant career advancement opportunities. [builtin.com](https://builtin.com/company/agzen)

## Sources
1. [agzen.com](https://www.agzen.com/) – Company overview, product, team
2. [agzen.com – What We Do](https://www.agzen.com/agzen-whatwedo) – Product details and trial results
3. [agzen.com – About Us](https://www.agzen.com/agzen-aboutus) – Mission, team, funding, partnerships
4. [builtin.com](https://builtin.com/company/agzen) – Culture, perks, headcount, founding year
5. [linkedin.com](https://www.linkedin.com/company/agzen) – Employee count, funding, locations, growth stats
6. AgFunder News (via search results) – Series A and Series B funding details, commercialization updates

## Other roles at AgZen

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