About Everest LabsRead all the information about this opportunity carefully, then use the application button below to send your CV and application. EverestLabs is an award-winning, venture-funded AI company building the intelligence and orchestration layer for the industrial materials economy. Fast Company and the Edison Awards have recognized us among the most innovative companies in sustainability and climate tech. We are a team of mission-driven engineers, builders and doers working toward one goal: no recyclable left behind. Our two product lines work in tandem: EverestLabs Robotics runs the industry's largest installed base of AI-powered, high-speed robotic sorting systems, built on purpose-built large vision models. Navigator is an agentic AI platform for plant operators. It combines edge vision AI, AI agents and plant automation so operators can see what is happening on every belt, understand why, and act on it, with the operator approving every action. Together they help MRFs, recyclers, packaging manufacturers and processing facilities get more value from infrastructure they already own: more throughput, less downtime and more recovered revenue.
About the Role:
The Sales & Deployment Engineer owns the technical side of a customer relationship from the first site survey to a live, performing deployment, across both Robotics and Navigator. You combine two jobs: the sales engineer who scopes and wins the deal, and the forward-deployed engineer who builds and ships the solution on the plant floor. You will walk MRFs and processing plants to see how material actually moves, design the right mix of robots, vision and AI agents, help the sales team close, and then make it work: partnering with our AI team to tune vision models to each site's streams, configuring Navigator agents, and driving go-live with our engineering and DevOps teams. This role suits someone equally comfortable talking throughput and contamination rates with a plant manager and shipping a working solution the same week. Because you sold it, you own making it real.
What You'll Do:
Win the DealRun site surveys. Visit MRFs, plastic and metal recyclers, and manufacturers to find robotics, vision and automation opportunities, and document line layouts, material streams and bottlenecks.
Translate pain into solutions. Work with operators to understand contamination, sortation accuracy, downtime, belt utilization and reporting gaps, and define what "solved" looks like in tons and dollars.
Design the solution. Recommend the right combination of robots, vision systems and Navigator integration level (line, process or plant) for each site.
Demo and educate. Lead product demonstrations, discovery workshops and technical presentations for plant executives, managers and floor supervisors.
Support proposals. Provide technical scope, feasibility, ROI and cost-benefit input so proposals match what the customer needs and what we can deliver.
Partner with sales. Review survey findings with account executives, shape deal strategy, handle technical objections and help close revenue targets.
Represent us in the field. Attend industry events and trade shows to help sales and marketing generate leads.
What You'll Do:
Deliver itOwn the deployment. Project-manage robotics installs and Navigator rollouts end to end, coordinating engineering, DevOps, field service and the customer on integration, infrastructure and go-live. Partner with the AI team on vision performance. Work with our AI team to tune models for each facility's material streams, cameras and conditions. You coordinate on-site data collection, relay customer requirements and validate results on the line; the AI team owns training and fine-tuning. Configure and customize AI agents. Adapt Navigator's agents, dashboards, alerts and artifacts to each plant's workflows, using coding agents to move fast without waiting on the core roadmap. Support plant integration. Help identify the right integration path, from alerts in existing workflows to signals, PLCs over OPC UA, and SCADA, and assist the engineering and controls teams who build those integrations, keeping the operator in control of every action. Onboard the customer. Partner with Customer Success so operators and managers adopt the system and see measurable results soon after go-live.
What You'll Do:
grow the account and close the loop Be the trusted technical advisor. Act as the customer's primary technical contact, answering questions and coordinating internal teams to resolve concerns. Expand the footprint. Spot upsell and cross-sell opportunities, such as adding Navigator to robot sites, adding robots to Navigator sites, or growing from one line to the whole plant. Feed product and engineering. Bring field learnings back so recurring pain points become platform features, not one-off fixes. Stay current. Track industry trends, competitor offerings and emerging technology in recycling, sorting and industrial AI, and share what you learn across sales, engineering and product.
What We're Looking For:
Bachelor's degree in mechanical, electrical, systems or computer engineering, computer science, or a related field, or equivalent experience.3+ years in a customer-facing technical role such as sales engineering, solutions engineering, forward deployment, implementation or technical consulting.
A track record of helping close technical deals and of taking solutions through to production.
Hands-on ability to build and customize software and AI solutions, including with coding agents. You ship, not just spec.
Strong project management across customer, engineering and DevOps stakeholders.
Ability to read technical specifications, line drawings and data sheets.
Excellent communication and presentation skills, with the ability to explain complex technology to both operators and executives.
Comfort working on-site in industrial environments, including on the plant floor in PPE.Willingness to travel up to 50% to customer facilities and industry events.
Skills and tools you'll likely draw onYou won't need every item; this is the landscape the role lives in.
Software and data: Python, SQL and scripting; REST APIs and webhooks; Git; Docker; a cloud platform (AWS, GCP or Azure); dashboards and BI tools (Grafana, Looker or similar).AI and ML: computer vision fundamentals (detection, classification); a working understanding of how models are labeled, trained and evaluated; LLM and agent frameworks; coding agents such as Claude Code or Cursor.
Hardware and industrial: industrial cameras and vision sensors; edge compute and GPU inference; networking basics; working familiarity with PLCs, SCADA and OPC UA; conveyors, optical sorters and robotic sorters.
Nice to Have:
Experience in MRFs, recycling, waste processing, materials handling, robotics or industrial automation.
Experience as a sales engineer at a technical SaaS or AI company.
Experience taking computer vision or ML systems into production.
Background deploying software into physical environments such as manufacturing, logistics or industrial IoT.Experience mentoring other engineers as the team grows.
Location and TravelThis is a US-based, remote-flexible role with a preference for candidates in the Central or Mountain regions; other US locations are considered. xhqgsiq Expect up to 50% travel to customer plants for site surveys, demos and deployments, plus industry events.
