We are hiring an additional member of Afresh’s Sales Engineering team to help up-level our sales process and execution, evangelize the differentiation and effectiveness of our new approach to managing the fresh supply chain, and drive the adoption of our growing product set. Afresh’s Sales Engineering team partners closely with our Sales and Account Management team, and collaborates cross-functionally with Operations, Product, Engineering, and Marketing. Our vision and expectation is that this individual will help build out the resources, processes, and documentation for our growing Sales Engineering team.

Role and Responsibilities:

• Work directly with prospects and customers to credibly communicate product differentiation, value, and technical functionality
• Lead operational and technical discovery to understand our customers’ business and map their needs to the Afresh solution
• Collaborate closely with Sales Directors and Account Managers on deal strategy, risks, and opportunities
• Consistently collate, deliver, and discuss product feedback from the field to our Product and Engineering teams
• Collaborate with Product Marketing to support new messaging/positioning and launch new products and enablement resources
• Maintain a deep understanding of competitive and complementary technologies and vendors, and how to position Afresh in relation to them
• Be a technical expert on all aspects of Afresh
• Document learnings extensively to engage and educate others

Skills and Experience:

• 3+ years of Sales Engineer experience, preferably working with Grocery or AI/ML-related products
• 5+ years of experience in a customer-facing role
• Experience managing end-to-end technical validation or POC process(es) of a technically complex SaaS product
• Demonstrated record of effectively collaborating with key stakeholders such as Account Managers and cross-functional leaders/teammates
• A true self-starter who is also comfortable dealing with ambiguity in a start-up environment where context changes rapidly
• Passion to solve unique, world-changing problems and be willing to go above and beyond to solve these problems
• Willingness to travel to work with prospective customers onsite, up to 30% travel

Nice to have:

• Experience with data architecture and ETL
• Consistently worked on strategic deals with companies with 10k+ employees or $500k+ ACV opportunities
  
  Cash base salary band in USD: $109,000 - 147,000. This position is a 70/30 split.
  This position is not eligible for immigration sponsorship.

The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities).

About the Role

As a Staff ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability. You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States.

What You'll Do:

• In your first 3 months, you'll partner with ML, Applied Science, and engineering leadership to identify the highest-leverage gaps in our ML platform and shape a multi-quarter technical strategy to close them.
• By the end of your first 6 months, you will have driven a platform-level initiative that meaningfully changes what's possible at Afresh — establishing the architecture for real-time inference across the company, redesigning model configuration and deployment end-to-end, or rebuilding our distributed inference layer for an order-of-magnitude growth in scale — while raising the bar across the ML org through design reviews and mentorship of other senior engineers.

Skills and Experience

• BS in Computer Science or a relevant technical field.
• 7+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
• Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
• You possess a genuine curiosity about ML modeling (e.g., demand forecasting, state estimation, ordering policy). You aren't just building "pipes"; you want to understand what is flowing through them. 
• You have a deep understanding of how scientists work and build tools that bridge the gap between a research notebook and production-grade software. 
• Technical leadership experience and a demonstrated ability to mentor junior engineers.
• Deep expertise in library design, API design, data structures, and algorithms.
• Strong familiarity with the Python ecosystem (NumPy, Pandas, Torch, PySpark). While our stack is Python-heavy, we value engineers who are stack-agnostic and focus on solving fundamental distributed systems problems. 
• Proven ability to architect high-throughput distributed inference systems using Spark, Dask, or Ray. 
• Experience in engineering robust data architectures with a focus on schema evolution and performance tuning. 
• Experience with end-to-end orchestration (lineage tracking, resource scheduling, self-healing pipelines).

Tech Stack: Our backend is pure Python (NumPy, Pandas, Torch, PySpark, Cython, orchestrated in Airflow). We use Databricks as our data warehouse. While we'd like you to have very good familiarity with Python, many of our problems are stack-agnostic.

This position is not eligible for company sponsorship.

Salary Band in Canada (CAD): $148,000 - $242,000

The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities).

About the Role

As a Staff ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability. You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States.

What You'll Do:

• In your first 3 months, you'll partner with ML, Applied Science, and engineering leadership to identify the highest-leverage gaps in our ML platform and shape a multi-quarter technical strategy to close them.
• By the end of your first 6 months, you will have driven a platform-level initiative that meaningfully changes what's possible at Afresh — establishing the architecture for real-time inference across the company, redesigning model configuration and deployment end-to-end, or rebuilding our distributed inference layer for an order-of-magnitude growth in scale — while raising the bar across the ML org through design reviews and mentorship of other senior engineers.

Skills and Experience

• BS in Computer Science or a relevant technical field.
• 7+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
• Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
• You possess a genuine curiosity about ML modeling (e.g., demand forecasting, state estimation, ordering policy). You aren't just building "pipes"; you want to understand what is flowing through them. 
• You have a deep understanding of how scientists work and build tools that bridge the gap between a research notebook and production-grade software. 
• Technical leadership experience and a demonstrated ability to mentor junior engineers.
• Deep expertise in library design, API design, data structures, and algorithms.
• Strong familiarity with the Python ecosystem (NumPy, Pandas, Torch, PySpark). While our stack is Python-heavy, we value engineers who are stack-agnostic and focus on solving fundamental distributed systems problems. 
• Proven ability to architect high-throughput distributed inference systems using Spark, Dask, or Ray. 
• Experience in engineering robust data architectures with a focus on schema evolution and performance tuning. 
• Experience with end-to-end orchestration (lineage tracking, resource scheduling, self-healing pipelines).

Tech Stack: Our backend is pure Python (NumPy, Pandas, Torch, PySpark, Cython, orchestrated in Airflow). We use Databricks as our data warehouse. While we'd like you to have very good familiarity with Python, many of our problems are stack-agnostic.

This position is not eligible for company sponsorship.

Salary Band in U.S. (USD): $169,000 - $273,000

The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities).

About the Role

As a Senior ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability. You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States.

What you will do:

• In your first 3 months, you might deliver a project that helps generalize model configuration, enables no-code model deploys for our various ML solutions, or vastly improves integration testing across our ML systems.
• By the end of your first 6 months, you will have owned the design and implementation of significant scalability improvements and additions to our ML platform. This might include new feature pipelines that power our recommendation engine, or work to stand up the first instance of real-time inference at Afresh.

Skills and Experience

• BS in Computer Science or a relevant technical field.
• 5+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
• Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
• You possess a genuine curiosity about ML modeling (e.g., demand forecasting, state estimation, ordering policy). You aren't just building "pipes"; you want to understand what is flowing through them. 
• You have a deep understanding of how scientists work and build tools that bridge the gap between a research notebook and production-grade software. 
• Technical leadership experience and a demonstrated ability to mentor junior engineers.
• Deep expertise in library design, API design, data structures, and algorithms.
• Strong familiarity with the Python ecosystem (NumPy, Pandas, Torch, PySpark). While our stack is Python-heavy, we value engineers who are stack-agnostic and focus on solving fundamental distributed systems problems. 
• Proven ability to architect high-throughput distributed inference systems using Spark, Dask, or Ray. 
• Experience in engineering robust data architectures with a focus on schema evolution and performance tuning. 
• Experience with end-to-end orchestration (lineage tracking, resource scheduling, self-healing pipelines).

Tech Stack: Our backend is pure Python (NumPy, Pandas, Torch, PySpark, Cython, orchestrated in Airflow). We use Databricks as our data warehouse. While we'd like you to have very good familiarity with Python, many of our problems are stack-agnostic.

This position is not eligible for company sponsorship.

Salary Range for Canada in CAD: $137,000 - $205,000

The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities).

About the Role

As a Senior ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability. You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States.

What you will do:

• In your first 3 months, you might deliver a project that helps generalize model configuration, enables no-code model deploys for our various ML solutions, or vastly improves integration testing across our ML systems.
• By the end of your first 6 months, you will have owned the design and implementation of significant scalability improvements and additions to our ML platform. This might include new feature pipelines that power our recommendation engine, or work to stand up the first instance of real-time inference at Afresh.

Skills and Experience

• BS in Computer Science or a relevant technical field.
• 5+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
• Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
• You possess a genuine curiosity about ML modeling (e.g., demand forecasting, state estimation, ordering policy). You aren't just building "pipes"; you want to understand what is flowing through them. 
• You have a deep understanding of how scientists work and build tools that bridge the gap between a research notebook and production-grade software. 
• Technical leadership experience and a demonstrated ability to mentor junior engineers.
• Deep expertise in library design, API design, data structures, and algorithms.
• Strong familiarity with the Python ecosystem (NumPy, Pandas, Torch, PySpark). While our stack is Python-heavy, we value engineers who are stack-agnostic and focus on solving fundamental distributed systems problems. 
• Proven ability to architect high-throughput distributed inference systems using Spark, Dask, or Ray. 
• Experience in engineering robust data architectures with a focus on schema evolution and performance tuning. 
• Experience with end-to-end orchestration (lineage tracking, resource scheduling, self-healing pipelines). 

Tech Stack: Our backend is pure Python (NumPy, Pandas, Torch, PySpark, Cython, orchestrated in Airflow). We use Databricks as our data warehouse. While we'd like you to have very good familiarity with Python, many of our problems are stack-agnostic.

This position is not eligible for company sponsorship.

Salary Range in U.S. $156,000 - $231,000

About the Role:

• Build and ship high quality applications to optimize in store operations and decision making.
• Collaborate with your engineering teammates to support thousands of grocery stores critical fresh food supply chains across the US.
• Working closely with product managers, designers, and our users, deliver great product experiences across the iPad, the web front-end, API, and data layers.
• Participate in and provide meaningful feedback about major design choices.
• Build out our analytics and monitoring/observability to understand our system behavior and make informed decisions.
• Ensure the quality of our software via automated tests
• Design and build UIs, APIs, and solutions that are reusable and extensible.
• Work alongside machine learning specialists to drive new feature development.

Skills and Experience

The following represents attributes our ideal candidate possesses. We encourage all highly qualified candidates to apply, even if they do not fulfill all the listed criteria.

• BS in Computer Science or equivalent experience
• 2+ years experience with full-stack web development, including some web front-end and API development
• Experience building & maintaining production level APIs and applications
• Collaborative attitude while also being highly self-directed
• Strong problem solving skills and excitement to tackle hard problems
• Enjoy working in a fast-paced, startup environment
• Required skills: TypeScript (or Javascript), React, and Python
• Nice-to-have skills: PostgreSQL, GraphQL, Databricks, DBT, Terraform/OpenTofu, Azure, pair programming, test-driven development

This position is not eligible for company sponsorship. 

Salary Range in Canada.: $136,000 - $205,000 (CAD)

About the Role:

• Build and ship high quality applications to optimize in store operations and decision making.
• Collaborate with your engineering teammates to support thousands of grocery stores critical fresh food supply chains across the US.
• Working closely with product managers, designers, and our users, deliver great product experiences across the iPad, the web front-end, API, and data layers.
• Participate in and provide meaningful feedback about major design choices.
• Build out our analytics and monitoring/observability to understand our system behavior and make informed decisions.
• Ensure the quality of our software via automated tests
• Design and build UIs, APIs, and solutions that are reusable and extensible.
• Work alongside machine learning specialists to drive new feature development.

Skills and Experience

The following represents attributes our ideal candidate possesses. We encourage all highly qualified candidates to apply, even if they do not fulfill all the listed criteria.

• BS in Computer Science or equivalent experience
• 2+ years experience with full-stack web development, including some web front-end and API development
• Experience building & maintaining production level APIs and applications
• Collaborative attitude while also being highly self-directed
• Strong problem solving skills and excitement to tackle hard problems
• Enjoy working in a fast-paced, startup environment
• Required skills: TypeScript (or Javascript), React, and Python
• Nice-to-have skills: PostgreSQL, GraphQL, Databricks, DBT, Terraform/OpenTofu, Azure, pair programming, test-driven development

This position is not eligible for company sponsorship.

Salary Range in U.S.: $156,000 - $231,00

About the Role

As a Senior Data Engineer, you’ll play a key role in scaling and improving how we integrate and process customer data. You will design and implement ETLs that reliably process large volumes of customer-provided data and build tools/improve the platform to make customer integrations faster, more accurate, and more scalable. You’ll also contribute to the development of new features that support our expanding product lines. Your work will have a direct and visible impact on our ability to onboard customers more easily and quickly and power our machine learning grocery solution.

What You’ll Do

• Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data.
• Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use.
• Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs.
• Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features.
• Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations.
• Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need.
• Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback.

What Makes You a Great Fit

We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification.

• Significant experience designing and maintaining ETLs that process large-scale datasets.
• Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
• Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
• A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
• Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
• A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
• Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences.
• Proven leadership in technical projects, with a willingness to mentor and help others grow.

Why Work Here

• Join a mission-driven company reducing millions of pounds of food waste in grocery stores per year.
• Work on challenging, real-world problems that have a direct impact on our customers.
• Be part of a collaborative, supportive team where your ideas are valued and acted on.
• Use cutting-edge tools and platforms to solve meaningful data challenges.

We’re looking for someone who thrives on tackling complex data problems and takes pride in building systems that work seamlessly at scale. If that sounds like you, we’d love to hear from you!

This position is not eligible for immigration sponsorship

Salary Range in Canada (CAD): $137,000 - $205,000

About the Role

As a Senior Data Engineer, you’ll play a key role in scaling and improving how we integrate and process customer data. You will design and implement ETLs that reliably process large volumes of customer-provided data and build tools/improve the platform to make customer integrations faster, more accurate, and more scalable. You’ll also contribute to the development of new features that support our expanding product lines. Your work will have a direct and visible impact on our ability to onboard customers more easily and quickly and power our machine learning grocery solution.

What You’ll Do

• Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data.
• Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use.
• Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs.
• Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features.
• Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations.
• Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need.
• Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback.

What Makes You a Great Fit

We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification.

• Significant experience designing and maintaining ETLs that process large-scale datasets.
• Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
• Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
• A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
• Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
• A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
• Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences.
• Proven leadership in technical projects, with a willingness to mentor and help others grow.

Why Work Here

• Join a mission-driven company reducing millions of pounds of food waste in grocery stores per year.
• Work on challenging, real-world problems that have a direct impact on our customers.
• Be part of a collaborative, supportive team where your ideas are valued and acted on.
• Use cutting-edge tools and platforms to solve meaningful data challenges.

We’re looking for someone who thrives on tackling complex data problems and takes pride in building systems that work seamlessly at scale. If that sounds like you, we’d love to hear from you!

This position is not eligible for immigration sponsorship

Salary Range in U.S.: $156,000 - $231,000

About the Role

As the Data Engineering Manager on the Core Data Engineering team, you'll lead the team responsible for integrating customers onto Afresh's platform and continuously improving the processes and code that make those integrations faster and more reliable. Your team will also build core dataflows that power new Afresh products as they launch.

This means owning the full lifecycle of customer data integrations: from raw data ingestion through transformation and delivery to downstream product and ML teams, across both new and existing grocery customers. Afresh's customer base is growing fast! We want to integrate customers across all of our products quickly and reliably. You'll drive integration execution, integration velocity, improve data quality and pipeline reliability, and build tooling and processes that make this process seamless.

This is a hands-on management role. You'll be deeply involved in technical decisions while also coaching your team, managing execution across multiple customer projects, and collaborating closely with Solutions Engineering, Product, and other engineering teams.

What You'll Do

• Lead and grow a team of data engineers, providing mentorship, technical guidance, and career development support.
• Own execution of customer integrations across multiple product lines (Store Ordering, RecsAPI, DC, Production Planning, and more), ensuring integrations are delivered on time and at a high quality bar.
• Build core dataflows that power new Afresh products, working closely with Product and ML teams to understand requirements and deliver reliable data foundations.
• Drive integration velocity: improve the speed and predictability of getting new customers from raw data landing to production-ready, leveraging AI tooling, standardized architecture, and strong contractor enablement.
• Continuously improve integration processes and shared code: identify patterns across customer integrations and invest in abstractions, templates, and automation that reduce per-customer effort over time.
• Collaborate deeply with Solutions Engineers, Product Managers, and customer-facing teams to scope integration work, unblock dependencies, communicate progress, and ensure integrations meet our customers’ needs.
• Improve data quality and pipeline reliability by investing in better alerting, self-healing patterns, and resilience to messy or incomplete customer data.
• Champion AI-forward engineering practices: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive tasks, and push the team to the bleeding edge of modern data engineering.
• Contribute technically: reviewing code and architecture decisions, pairing with engineers on complex problems, and staying close to the work.

What Makes You a Great Fit

We encourage all highly-qualified candidates to apply, even if they don't meet every listed qualification.

• 3+ years of engineering management experience
• Strong technical background in data engineering: experience with Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar).
• Track record of shipping high-quality data integrations or ETL systems at scale, and a deep understanding of what makes data pipelines reliable.
• Experience managing execution across multiple concurrent projects with different customers or stakeholders, balancing competing priorities with clear communication.
• Demonstrated ability to improve team velocity through better tooling, process improvements, or automation.
• Genuine enthusiasm for AI-augmented engineering workflows. You've experimented with AI coding tools, agentic workflows, or similar, and have a vision for how they can transform data engineering and uplevel the team.
• Comfort working with messy, real-world data from enterprise customers, and the pragmatism to ship solutions that work without over-engineering.
• Strong collaboration skills: you're effective working across engineering, product, and customer-facing teams in a fast-paced environment.

Nice to Have

• Experience in grocery, retail, or supply chain data domains.
• Prior experience at a high-growth startup navigating rapid customer expansion.

Our Tech Stack

• Python, PySpark, dbt
• Databricks (Delta Lake, Unity Catalog)
• Astronomer (Airflow) for orchestration
• Claude, GitHub, Shortcut, Notion for development workflows

Why Work Here

• We are a mission-driven company that reduces millions of pounds of food waste (and growing!) in grocery stores every year.
• Work on challenging, real-world data problems that have a direct and visible impact on customers.
• Be part of an engineering culture that's genuinely AI-forward. We want to be on the bleeding edge.
• Lead a team at a pivotal inflection point: rapid customer growth means your work directly shapes how Afresh scales.
• Collaborative, supportive environment & awesome people :)

This position is not eligible for company sponsorship.

Salary Range in Canada (CAD): $157,433 - $232,996

About the Role

As the Data Engineering Manager on the Core Data Engineering team, you'll lead the team responsible for integrating customers onto Afresh's platform and continuously improving the processes and code that make those integrations faster and more reliable. Your team will also build core dataflows that power new Afresh products as they launch.

This means owning the full lifecycle of customer data integrations: from raw data ingestion through transformation and delivery to downstream product and ML teams, across both new and existing grocery customers. Afresh's customer base is growing fast! We want to integrate customers across all of our products quickly and reliably. You'll drive integration execution, integration velocity, improve data quality and pipeline reliability, and build tooling and processes that make this process seamless.

This is a hands-on management role. You'll be deeply involved in technical decisions while also coaching your team, managing execution across multiple customer projects, and collaborating closely with Solutions Engineering, Product, and other engineering teams.

What You'll Do

• Lead and grow a team of data engineers, providing mentorship, technical guidance, and career development support.
• Own execution of customer integrations across multiple product lines (Store Ordering, RecsAPI, DC, Production Planning, and more), ensuring integrations are delivered on time and at a high quality bar.
• Build core dataflows that power new Afresh products, working closely with Product and ML teams to understand requirements and deliver reliable data foundations.
• Drive integration velocity: improve the speed and predictability of getting new customers from raw data landing to production-ready, leveraging AI tooling, standardized architecture, and strong contractor enablement.
• Continuously improve integration processes and shared code: identify patterns across customer integrations and invest in abstractions, templates, and automation that reduce per-customer effort over time.
• Collaborate deeply with Solutions Engineers, Product Managers, and customer-facing teams to scope integration work, unblock dependencies, communicate progress, and ensure integrations meet our customers’ needs.
• Improve data quality and pipeline reliability by investing in better alerting, self-healing patterns, and resilience to messy or incomplete customer data.
• Champion AI-forward engineering practices: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive tasks, and push the team to the bleeding edge of modern data engineering.
• Contribute technically: reviewing code and architecture decisions, pairing with engineers on complex problems, and staying close to the work.

What Makes You a Great Fit

We encourage all highly-qualified candidates to apply, even if they don't meet every listed qualification.

• 3+ years of engineering management experience
• Strong technical background in data engineering: experience with Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar).
• Track record of shipping high-quality data integrations or ETL systems at scale, and a deep understanding of what makes data pipelines reliable.
• Experience managing execution across multiple concurrent projects with different customers or stakeholders, balancing competing priorities with clear communication.
• Demonstrated ability to improve team velocity through better tooling, process improvements, or automation.
• Genuine enthusiasm for AI-augmented engineering workflows. You've experimented with AI coding tools, agentic workflows, or similar approaches, and you have a vision for how they can transform data engineering and uplevel the team.
• Comfort working with messy, real-world data from enterprise customers, and the pragmatism to ship solutions that work without over-engineering.
• Strong collaboration skills: you're effective working across engineering, product, and customer-facing teams in a fast-paced environment.

Nice to Have

• Experience in grocery, retail, or supply chain data domains.
• Prior experience at a high-growth startup navigating rapid customer expansion.

Our Tech Stack

• Python, PySpark, dbt
• Databricks (Delta Lake, Unity Catalog)
• Astronomer (Airflow) for orchestration
• Claude, GitHub, Shortcut, Notion for development workflows

Why Work Here

• We are a mission-driven company that reduces millions of pounds of food waste (and growing!) in grocery stores every year.
• Work on challenging, real-world data problems that have a direct and visible impact on customers.
• Be part of an engineering culture that's genuinely AI-forward. We want to be on the bleeding edge.
• Lead a team at a pivotal inflection point: rapid customer growth means your work directly shapes how Afresh scales.
• Collaborative, supportive environment & awesome people :)

This position is not eligible for company sponsorship.

Salary Range in U.S.: $ 179,469 - $262,811

Sr. Talent Acquisition Partner

About the Role

As the Senior Talent Acquisition Partner at Afresh, you’ll act as a strategic partner to our hiring managers, identifying the technical talent necessary to drive our mission forward.

We’re looking for a high-impact closer—someone who thrives on sourcing niche technical talent and takes pride in high close rates and aggressive time-to-fill metrics. You leverage the latest AI recruitment tooling to automate recruiting pipelines & are ATS and operationally minded.

You are a consultative partner who constructive strategizes & pushes back with hiring managers and executives to drive the success of scaling hires. You know that top engineers are skeptical of low-effort outreach, so you lead with high-signal, technically credible communication—not 'rockstar' clichés. If you’re a full-cycle expert who knows how to move the needle on technical headcount while maintaining an elite candidate experience, this could be the perfect role for you!

Key Responsibilities:

• Build relationships and collaborate with business leaders, hiring managers, and HR colleagues to identify hiring needs, refine job descriptions , and develop talent acquisition strategies for openings at all levels.
• Serve as a candid advisor to hiring managers to define roles and ideal profiles—including raising the bar on expectations and pushing back on requirements that are unrealistic or that will unnecessarily constrain the pipeline.
• Recruit for open roles leveraging a full range of sourcing channels including referrals, internal employees, Linkedin Recruiter, and the latest AI recruitment tooling. You engage passive talent where they actually live including looking at GitHub profile reviews, Stack Overflow contributions, niche Slack communities, and Discord servers.
• Plan and execute full-cycle recruiting. Manage the end-to-end recruiting process for technical positions, from sourcing and screening to interviewing and extending and closing offers. Ensure a smooth, efficient, communicative, and positive experience for all candidates.
• Ensure hiring with excellence by conducting discovery calls with candidates for alignment on compensation requirements to ensure successful offer acceptance and ultimate hire.
• Create exceptional candidate and hiring manager experiences by identifying and anticipating needs, following issues to closure, and collaborating with key stakeholders and exceeding expectations.
• Be excited about AI tooling & the impact AI can have in identifying talent and streamlining the recruitment workflow; test new theories & ideas, and try new AI technology.
• Ideal candidate can seamlessly pivot between technical roles (Software Engineering, Data Science, Product) and GTM roles (Sales, Marketing, Account Management).
• Own our ATS (Greenhouse). You will ensure data integrity, optimize workflows, and use the platform to provide transparent reporting to stakeholders.
• Must be analytics driven, building reports for the executive team on pipeline health, time-to-fill, offer acceptance rate, and cost-per-hire.
• Ensure all job postings and hiring practices remain compliant with local and federal labor laws in partnership with HR.
• Deliver Process Excellence. Facilitate interview debriefs, drive decision-making, and maintain a high bar for candidate experience.
• All other duties and projects, as assigned.

Who You Are

• You have 7+ years of experience in full-cycle recruiting, ideally in a high-growth startup environment where you’ve had to be self-sufficient.
• You are “Technically Fluent” ie. you know the difference between Python and JavaScript, understand why React is a library and not a language, and can explain a basic software development lifecycle. You don't write code—but you can hold a credible conversation with the people who do.
• You don’t just wait for applicants. You are a pro at LinkedIn and other sourcing tools and enjoy finding creative ways to reach passive talent.
• You understand how to spot a high-performing Revenue talent and know what it takes to sell a mission-driven product.
• You understand the art of the offer. You can navigate complex compensation conversations and equity explanations with ease.
• You're honest about the pros and cons of joining Afresh—you know that authentic sells close better than hype. And you're genuinely curious about technology, keeping up with new frameworks and industry shifts not because you have to, but because it makes you better at your job.
• You have the ability to work independently, manage multiple roles concurrently, and prioritize effectively.
• You have the proven ability to manage 15+ active, high-touch candidates simultaneously without letting anyone fall through the cracks.
• You are an expert closer with a proven track record of driving high offer-acceptance rates and drastically reducing time-to-fill through expert negotiation and proactive candidate management.
• You're process oriented. Whether it's execution or designing existing process improvements, you thrive in the details.
• Bachelor’s degree required.

This position is not eligible for company sponsorship.

Salary Range in U.S: $122,000 - $183,000

About the Role

As the Product Manager for Store Operations, you’ll own our next generation store-level solution. You'll own user and market research for this area, and you'll work with beta customers, early adopters, sales and marketing to take this product area to market. You'll work closely with product design, machine learning engineers, and mobile and full-stack engineers to create a holistic experience that works end to end. Your ownership, attention to detail, and your obsession with outcomes will lead to both short and long term rewards: every incremental bit of performance you deliver will directly result in less food waste.

What You’ll Do

• Own our next generation inventory management and store ordering solution that will be responsible for ordering 25%+ of fresh food volume in grocery in the US, eliminating 100s of millions of pounds of food waste (with the potential to grow that to billions)
• Own your product vision and roadmap, including the ML models, end to end app experience, monitoring and reporting, and data validation.
• Communicate both the business and technical rationale behind your decisions. Evangelize your vision and excite others with where you want to take your product.
• Deeply understand the market and our customers in order to build products that deliver massive value to our customers and the broader fresh food ecosystem.
• Work cross-functionally with Operations, Engineering, Design, Marketing, and Commercial to realize our product vision by taking products from conception to launch.
• Build strong relationships with partners and customers in order to inform roadmap and product prioritization.
• Develop user stories and product requirements, engage in usability and prototype testing, and define and monitor success metrics for maximal impact.

Skills and Experience

The following represent the skills and experience our ideal candidate possesses. We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.

• 3+ years of demonstrated success as a Product Manager, launching and scaling customer-facing software that achieved measurable business outcomes
• Technical fluency that enables you to creatively explore possibilities and challenge constraints with engineering, with demonstrated ability to earn the respect of talented engineers.
• Strong analytical skills, with the ability to gather data, both qualitative and quantitative, emerge with insights, and make and communicate well-reasoned decisions.
• Excellent communication skills, logical reasoning, and storytelling, with proven ability to collaboratively work across a variety of stakeholders.
• Experience creating product roadmap(s) from conception to launch, driving product vision, defining go-to-market strategy and leading design discussions.
• Experience with rapidly creating prototypes using generative coding tools.

Nice To Haves

• Experience with process management software

This position is not eligible for immigration sponsorship

This is a Hybrid position based in San Francisco, CA 

Salary Band for U.S.: $143,055 - $193,545

About the Role

As the Senior Product Manager for Store Ordering, you'll be the strategic owner of our flagship store ordering product suite, used by tens of thousands of grocery departments nationwide. You'll define the product vision and multi-quarter roadmap, drive cross-functional alignment across engineering, ML, design, data, and commercial teams, and be accountable for the business outcomes of a solution already driving hundreds of millions of pounds of food waste reduction each year. You'll mentor and guide other PMs and cross-functional partners, set the standard for product excellence, and ensure that both near-term execution and long-term strategy are tightly aligned with Afresh's mission and commercial goals.

What You'll Do

• Own the product vision, strategy, and multi-quarter roadmap for Store Ordering, aligning it with company-level goals and commercial priorities.
• Drive performance, reliability, and measurable shrink and sales impact across the Store Ordering suite.
• Lead roadmap prioritization with a strong strategic lens, balancing customer commitments, technical investments, and new value creation with clear, data-driven trade-offs.
• Partner deeply with Data and ML teams to evolve forecasting and ordering policies, define guardrails, and proactively identify opportunities to push the frontier of ordering accuracy.
• Shape and drive the strategy for adherence and input quality, including display controls, overrides, and detection of anomalous user behavior.
• Lead large-scale, cross-functional delivery and change management for multi-chain rollouts, coordinating across engineering, design, data, and customer-facing teams.
• Set the bar for operational excellence at scale: define and own SLAs, incident response processes, telemetry and alerting strategies, and on-call playbooks.
• Serve as a trusted partner to key customer stakeholders; translate deep customer insight into product strategy. Own impact storytelling and support GTM on renewals and expansions.
• Define and track key success metrics—accuracy, adoption, adherence, and business impact—and use them to drive continuous improvement.
• Represent Store Ordering in leadership forums, influencing company-wide product and technical strategy.

Skills and Experience

• 5+ years as a PM shipping customer-facing software, with significant experience owning and scaling a mature, in-market product.
• Demonstrated ability to set product vision and strategy, not just execute on a roadmap—experience defining multi-quarter plans and aligning cross-functional leadership.
• Track record of driving measurable business outcomes through product improvements: shipping incremental, low-risk rollouts while also making strategic bets.
• Strong technical fluency: deep understanding of web and mobile architecture, comfortable reading and working with API specs, writing SQL, and engaging meaningfully with engineers and ML practitioners.
• Sophisticated analytical decision-making: skilled at defining metrics frameworks, synthesizing qualitative and quantitative signals, and designing A/B tests or phased rollouts to de-risk changes.
• Ownership mindset at a senior level: proactive leadership on incidents, SLAs, alerting, on-call coordination, and driving systemic fixes—not just one-off resolutions.
• Excellent communicator who writes crisp PRDs, strategy docs, and change specs, and can influence and align senior stakeholders across product, engineering, commercial, and leadership.
• Experience with rapidly creating prototypes using generative coding tools.
• Experience working in supply chain, grocery, retail, or other operationally complex domains is a strong plus.

We encourage all highly qualified candidates to apply, even if you don’t meet every bullet.

This position is not eligible for immigration sponsorship.

This is a 100% remote, United States based position based out of one of the eligible states listed below.

Salary Band for U.S.: $159,120 - 238,680

About the Role As a Lead Solutions Engineer at Afresh, you will work directly with our grocery retail partners and Afresh colleagues to deploy our purpose-built fresh food solution and bring tangible, lasting impact to our partners.

Externally, you will build effective partnerships with customers to drive the success of end-to-end integrations. You will apply a skillset at the intersection of data architecture, operations, and predictive analytics to translate customers' business needs into technical design for integration to the Afresh platform. Internally, you'll collaborate cross-functionally and act as a connecting force between our integration technology and customers' operational reality.

You have experience managing customer relationships and leading technical projects in fast-paced environments. You are excited to reduce fresh food waste in the grocery industry, and help the planet in the process!

What You'll Do A typical day might involve discussing data architecture with engineers, digging into customer data, and developing technical implementation strategies and specifications. Specifically, you will:

• Own and execute integration projects from discovery through go-live — creating detailed project plans with milestones, risk mitigation, and success criteria, and coordinating internal and customer-facing stakeholders through each phase
• Apply deep knowledge of Afresh's core data model and integration patterns to evaluate whether customer needs can be met through standard approaches; flag misalignments and propose adjustments to design or the customer's approach
• Independently lead technical discovery and design calls with customers, mapping their workflows and systems to the Afresh platform and drafting detailed design documentation that aligns IT stakeholders and internal Engineering on the proposed ETL design
• Analyze complex data relationships, identify root causes of mismatches or anomalies, and build custom queries or lightweight tools to streamline validation and data mapping work
• Collaborate with data engineering, product engineering, and data science to drive integration delivery; surface technical risks and ambiguities early and work cross-functionally to resolve them
• Influence internal discussions with thoughtful input and context from customer needs; share learnings across Product, Sales, and Customer Success
• Contribute to team documentation, templates, and onboarding content; mentor junior team members and take initiative on process improvements

Skills and Experience

• Demonstrated ability to independently own and execute complex integration projects end-to-end, including scoping, stakeholder coordination, and on-time delivery
• Experience leading technical discovery and solution design with customer IT stakeholders, including drafting design documentation and guiding customers through technical trade-offs
• Data transformation and design experience, with proven ability to work alongside data engineers, data scientists, and subject matter experts to manage and implement customer integration requirements
• This role is ideal for someone who is strong in internal technical project management and also excels in client-facing situations
• Strong organizational skills, high attention to detail, and ability to communicate clearly across levels and profiles
• Proficiency in SQL, Excel, and other analytical tools
• Ability to continuously learn, work independently, and make decisions with appropriate escalation to keep projects on track
• Open to travel (up to 10%)

Nice to Have

• Experience with AI/ML systems and identifying issues with data inputs used in predictive analysis
• Commercial mindset that allows you to understand and act on what customers care about most
• Dedication to quality, testing, design processes, automation, and operational excellence

This position is not eligible for work sponsorship.

Salary Range in U.S.: $134,000 - $181,000

About the Role

As an Enterprise Account Executive at Afresh, you will focus on strategic, enterprise sales with large grocers throughout the US. You'll identify and articulate how Afresh can unlock significant value for their business. As a  part of the Sales team at a rapidly growing startup, you'll have the opportunity to help define our processes, influence strategic decisions, and help develop the sales culture.

• Execute all aspects of the sales cycle while building and managing relationships with key, executive-level decision-makers at various grocers
• Manage and run complex sales cycles while guiding customers through every aspect of the sales process from initial contact to close
• Prospect for new clients, build and deliver product presentations, and develop proposals
• Develop a deep understanding of the Afresh product, competitive landscape, the grocery market, and our customers’ needs and pain points
• Partner closely with teams such as Product, Engineering, Implementation, and Customer Success to deliver a world-class customer experience

Skills and Experience

The following represents attributes our ideal candidate possesses. We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.

• 10+ years of overall sales or customer-facing experience at B2B companies
• 5+ years of direct AI or SaaS sales experience with annual contract values >$1M
• Experience with data heavy products and industries at the forefront of an industry
• Startup or growth company experience between $10M and $100M of sales a plus
• Experience in retail broadly required and grocery, food distribution or the food supply chain a plus
• Experience selling complex meaningful technological or SaaS-based systems in enterprise-level partnerships to VP / C-suite stakeholders
• Experience collaborating with cross-functional teams through deal processes, multi-threading, and building champions in multiple organizations
• Highly organized, detail-oriented, and data-driven with a demonstrated ability to accurately forecast sales pipeline and results
• A true self-starter who works well in ambiguity and effectively adopts change

Salary Compensation in USD: $150,000 - $175,000

50/50 split, $300k - $350k OTE

#LI-REMOTE

About the Role 

As a Senior Revenue Operations Analyst, you will be the engine behind our revenue data and go-to-market systems. Reporting to the Manager of Sales Operations & Engineering, you will bridge the gap between our raw data and strategic decision-making, ensuring our Sales, Sales Engineering, Customer Success, and Marketing teams have the tools and insights they need to scale. You will be the primary steward of our tech stack and own the source of truth for our performance metrics, serving as an operational bedrock of all revenue growth at Afresh.

Key Responsibilities

• Systems Architecture & Maintenance: Manage and optimize the RevOps tech stack (Salesforce, HubSpot, etc.), ensuring high data integrity and seamless synchronization across platforms.
• Performance Insight & Reporting: Build, maintain, and interpret centralized KPI dashboards, identifying trends, bottlenecks, and opportunities in our pipeline.
• Process Optimization: Partner with Revenue teams to refine workflows, reducing friction in the sales cycle and improving deal velocity.
• Forecasting Support: Provide the quantitative foundation for revenue forecasting and pipeline reviews, ensuring leadership has accurate, real-time data for growth decisions.
• Revenue Integrity: Work closely with Finance and Customer Success to audit bookings and billings, automating and upgrading operational flows.
• Data Hygiene & Governance: Serve as the primary point of contact for Salesforce hygiene, implementing validation rules and processes that keep our CRM actionable and clean.

Key AI Responsibilities

• Experience implementing automation and AI-driven insights in revenue operations workflows.
• Proven track record of integrating AI tools with CRM and GTM technology stacks.
• Built and maintained AI-driven dashboards and reporting to surface actionable insights across sales, marketing and account management.

Key Sales Enablement Responsibilities

• Design and maintain the process for sales training; facilitate the creation of documentation, playbooks, and onboarding sequences that ensure proficiency in our GTM teams. 

Salary Band in USD: $130,000 - $150,000 + 10% variable

The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities).

About the Role

As an ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability. You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States.

What You'll Do

• In your first 3 months, you might deliver a feature that helps generalize model configuration, enables no-code model deploys for our various ML solutions, or vastly improves integration testing across our ML systems.
• By the end of your first 6 months, you will have owned the implementation of significant scalability improvements and additions to our ML platform. This might include new feature pipelines that power our recommendation engine, or work to stand up the first instance of real-time inference at Afresh.

Skills and Experience

• BS in Computer Science or a relevant technical field.
• 3+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
• Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
• Deep expertise in library design, API design, data structures, and algorithms.
• Strong familiarity with Python.

Tech Stack: Our backend is pure Python (NumPy, Pandas, Torch, PySpark, Cython, orchestrated in Airflow). We use Databricks as our data warehouse. While we'd like you to have very good familiarity with Python, many of our problems are stack-agnostic.

This position is not eligible for company sponsorship.

Salary Band in Canada: $114,00 - 154,000

Salary Band in U.S.: $130,000 - $176,000