NumPy Jobs in Canada.
All active NumPy roles based in Canada.
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Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.
We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!
Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd!
About the opportunity
We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization.
What You Will Be Doing
- Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
- Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
- Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
- Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
- Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
- Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
- Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
- Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.
What You Bring
- Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
- Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
- SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
- dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
- Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
- Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
- Business Intelligence Tools: Strong skills in Looker data visualization and LookML (including familiarity with Looker’s conversational AI and data agent capabilities) or similar BI tools.
- AI Agents & Automation: Experience with AI agents or generative AI tools to optimize workflows and service delivery (such as creating chatbots or automated analytic assistants) is a plus.
- Real-Time & Streaming Data: Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis, Spark Streaming) for handling continuous data flows.
- Programming: Proficient in Python for data analysis and manipulation (pandas, NumPy, etc.), with the ability to write clean, efficient code. Experienced with shell scripting and command-line tools for automating workflows and data processing tasks.
- ETL/Orchestration: Familiarity with ETL processes and workflow orchestration tools like Apache Airflow (or similar scheduling tools) for automating data pipelines alongside Docker for local development and testing.
- Cloud Platforms: Experience with cloud platforms and services (especially AWS or GCP) for data storage, compute, and deployment.
- Version Control & CI/CD: Solid understanding of code versioning (Git) and continuous integration/continuous deployment (CI/CD) processes in a data engineering context.
- Agile Methodology: Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment.
- Soft Skills: Excellent communication and presentation skills, with critical thinking and problem-solving abilities. Proven track record of working effectively on cross-functional teams and translating business needs into technical solutions.
- Data Governance & Ethics: Experience implementing data governance best practices, ensuring data quality and consistency. Knowledge of data ethics, bias mitigation strategies, and data privacy regulations (e.g., GDPR, CCPA) with a commitment to compliance.
Nice to Have
- Community & Open Source: Contributions to open-source projects or active participation in data community initiatives.
- AI/ML Skills: Experience with applying Artificial Intelligence/Machine Learning techniques in analytics (e.g., building predictive models for forecasting, churn prediction, fraud detection, etc.). Practical experience deploying models and using MLOps/DataOps practices for lifecycle management.
- Statistical Background: Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments.
- Additional Programming: Knowledge of additional programming or query languages (e.g., R, Scala, Julia, Spark SQL) that can be applied in analytics workflows.
- Certifications: Certifications in relevant data technologies or cloud platforms (such as Snowflake, AWS, GCP, or Looker) demonstrating your expertise.
The ideal candidate will be a self-starter with a passion for data and analytics, capable of navigating complex datasets to uncover valuable insights. They should be comfortable working in a fast-paced environment, adapting to new technologies, and driving innovation in our data practices.They should be able to navigate complex data landscapes, uncover meaningful insights, and communicate these findings effectively to both technical and non-technical audiences. The ability to stay current with industry trends and continuously learn new technologies is essential in this role.
This role offers the opportunity to make a significant impact on our organization's data strategy and contribute to critical business decisions through advanced analytics. The successful candidate will play a key role in shaping our data culture and driving the adoption of cutting-edge data technologies and methodologies.
If you are a data enthusiast with a track record of delivering impactful analytics solutions and a desire to push the boundaries of what's possible with data, we want to hear from you!
The base salary range for this position is $81,990 to $91,100. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits.
Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.
We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.
Tucows and its subsidiaries participate in the E-verify program for all US employees.
Learn more about Tucows, our businesses, culture and employee benefits on our site here.
Ready to apply?
Apply to Tucows
Analytics Engineer
Share this job
Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.
We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!
Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd!
About the opportunity
We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization.
What You Will Be Doing
- Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
- Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
- Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
- Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
- Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
- Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
- Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
- Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.
What You Bring
- Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
- Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
- SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
- dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
- Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
- Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
- Business Intelligence Tools: Strong skills in Looker data visualization and LookML (including familiarity with Looker’s conversational AI and data agent capabilities) or similar BI tools.
- AI Agents & Automation: Experience with AI agents or generative AI tools to optimize workflows and service delivery (such as creating chatbots or automated analytic assistants) is a plus.
- Real-Time & Streaming Data: Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis, Spark Streaming) for handling continuous data flows.
- Programming: Proficient in Python for data analysis and manipulation (pandas, NumPy, etc.), with the ability to write clean, efficient code. Experienced with shell scripting and command-line tools for automating workflows and data processing tasks.
- ETL/Orchestration: Familiarity with ETL processes and workflow orchestration tools like Apache Airflow (or similar scheduling tools) for automating data pipelines alongside Docker for local development and testing.
- Cloud Platforms: Experience with cloud platforms and services (especially AWS or GCP) for data storage, compute, and deployment.
- Version Control & CI/CD: Solid understanding of code versioning (Git) and continuous integration/continuous deployment (CI/CD) processes in a data engineering context.
- Agile Methodology: Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment.
- Soft Skills: Excellent communication and presentation skills, with critical thinking and problem-solving abilities. Proven track record of working effectively on cross-functional teams and translating business needs into technical solutions.
- Data Governance & Ethics: Experience implementing data governance best practices, ensuring data quality and consistency. Knowledge of data ethics, bias mitigation strategies, and data privacy regulations (e.g., GDPR, CCPA) with a commitment to compliance.
Nice to Have
- Community & Open Source: Contributions to open-source projects or active participation in data community initiatives.
- AI/ML Skills: Experience with applying Artificial Intelligence/Machine Learning techniques in analytics (e.g., building predictive models for forecasting, churn prediction, fraud detection, etc.). Practical experience deploying models and using MLOps/DataOps practices for lifecycle management.
- Statistical Background: Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments.
- Additional Programming: Knowledge of additional programming or query languages (e.g., R, Scala, Julia, Spark SQL) that can be applied in analytics workflows.
- Certifications: Certifications in relevant data technologies or cloud platforms (such as Snowflake, AWS, GCP, or Looker) demonstrating your expertise.
The ideal candidate will be a self-starter with a passion for data and analytics, capable of navigating complex datasets to uncover valuable insights. They should be comfortable working in a fast-paced environment, adapting to new technologies, and driving innovation in our data practices.They should be able to navigate complex data landscapes, uncover meaningful insights, and communicate these findings effectively to both technical and non-technical audiences. The ability to stay current with industry trends and continuously learn new technologies is essential in this role.
This role offers the opportunity to make a significant impact on our organization's data strategy and contribute to critical business decisions through advanced analytics. The successful candidate will play a key role in shaping our data culture and driving the adoption of cutting-edge data technologies and methodologies.
If you are a data enthusiast with a track record of delivering impactful analytics solutions and a desire to push the boundaries of what's possible with data, we want to hear from you!
The base salary range for this position is $81,990 to $91,100. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits.
Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.
We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.
Tucows and its subsidiaries participate in the E-verify program for all US employees.
Learn more about Tucows, our businesses, culture and employee benefits on our site here.
Ready to apply?
Apply to Tucows Inc.
Insights & Integrations Consultancy, Data Scientist Intern(Fall/September 2026, 12 Months)
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Who we are:
Who you are:
We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Scientist Intern within the Insights & Integrations Consultancy team that will support ongoing projects by assisting in data analysis, visualization, and the development of solutions that help optimize fleet operations and enhance customer decision-making. If you love technology and are keen to join an industry leader — we would love to hear from you!
What you'll do:
As a Data Scientist Intern within the Insights & Integrations Consultancy team, you will gain hands-on experience in leveraging data to drive strategic insights for customers and partners. In this role, you will have the opportunity to work with Geotab’s open data platform, learning how to explore and interpret telematics data to solve real-world business challenges. You will collaborate with cross-functional teams, including Data Scientists, Product Managers, and Integration Engineers, to support key initiatives focused on portfolio expansion, retention, and solution innovation.
Throughout your internship, you will develop a deeper understanding of industry trends, fleet analytics, and Geotab’s ecosystem, while contributing to meaningful projects that have a direct impact on customers and partners.
The opportunity:
- 12 month work-term beginning September 2026.
- Full-time, paid internship: Monday - Friday, 37.5hrs/week.
- Your first week at Geotab begins with 'GEO Launch' - a one-week Employee Orientation. Click here to learn more!
- Learn more about the Geotab Campus Program here.
- This posting is for an existing vacancy.
How you'll make an impact:
- Develop foundational knowledge of the Geotab ecosystem and telematics data, assisting in data exploration, visualization, and analysis to support customer and partner insights.
- Collaborate with Data Scientists and cross-functional teams to optimize the use of Geotab’s technology, providing analytical support for ongoing projects.
- Assist in building and refining data-driven dashboards for internal and external stakeholders, facilitating informed decision-making.
- Support continuous improvement initiatives by gathering feedback, identifying trends, and contributing to data-driven recommendations.
- Work closely with mentors to apply statistical and machine learning techniques in fleet analytics, helping develop predictive models and insights under guidance.
- Contribute to proof-of-concept development, assisting in the creation of small-scale models or prototypes that demonstrate the feasibility and impact of analytics-driven solutions.
- Stay informed on industry trends, emerging data science techniques, and best practices to enhance analytical capabilities.
- Maintain and update documentation on data analysis processes, methodologies, and findings for internal knowledge-sharing.
- Assist in maintaining data pipelines using SQL and Python-based workflows to support ongoing analytics initiatives.
What you'll bring to the role:
- Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Basic experience with Python for data analysis or automation (e.g., pandas, NumPy, or scikit-learn).
- Familiarity with SQL and working with structured datasets.
- Strong analytical and problem-solving skills, with an eagerness to learn how to extract insights from large datasets.
- Interest in data visualization and storytelling, with exposure to tools like Power BI, Tableau, or Matplotlib.
- Ability to communicate findings clearly to both technical and non-technical audiences.
- Strong attention to detail and organizational skills, with the ability to manage multiple tasks.
- Willingness to collaborate and work in a team-oriented environment.
- Curiosity about emerging data science trends and a passion for applying analytics to solve real-world problems.
How we work:
This role offers an hourly pay range which is anticipated to be the range listed below. The actual pay for this position depends on a variety of factors such as but not limited to student's academic program, relevant experience, and location. Geotab is committed to fair and equitable compensation and will share final details as part of the offer process. All offers of employment are contingent upon proof of eligibility to work for the duration of the internship and the individual's ability to pass a background check.
Ready to apply?
Apply to Internship List
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
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
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
Ready to apply?
Apply to Afresh
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
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
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
Ready to apply?
Apply to Afresh
Narvar is growing! We are hiring a Senior Software Engineer II to build new products and improve all aspects of the Narvar platform. Data is at the core of our competitive advantage so the work you do has a large impact across the company, our business partners, and the lives of our end users.
Machine Learning Engineers at Narvar work across the stack. We are ‘full-stack’ ML Engineers. This means that we write production-level code and own machine learning operations for our teams.
Day-to-day
- Design and deploy machine learning algorithms for use cases spanning e-commerce, consumer trends, markets, logistics, and new products
- Work on real-world consumer data for natural language processing, image classification, time series analysis, outlier detection, user modeling, etc
- Work with large unstructured data
- Be at the intersection of mathematics, machine learning, business, and computer science and impact millions of users through your work
- Multiply the effect of your data science and data team members by building frameworks, tools, and methodologies that the entire team use
- Provide thought leadership to a team through high quality write-ups, reviews, and a strong vision grounded in practical experience and a wider industry view
What we’re looking for
- Strong machine learning skills.
- Fluency in Python, PyTorch, Tensorflow, Pandas, numpy, and machine learning packages
- Data Engineering skills and large data experience. You should have dealt with large amounts of data (TB) in a production setting, built world class data pipelines using cutting edge tools (e.g. Spark).
- 10+ years of hands-on experience shipping models to production, working on a variety of problem spaces (eg: user modeling, spam classification, prediction, clustering etc)
- MS in Computer Science, Statistics, Math, Science (physical or social), Engineering or similar quantitative and computation field plus 5+ years of industry experience
- Strong software engineering and coding skills with the ability to write production quality code
- Strong understanding of probability & statistics, machine learning, and algorithms
- Experience with SQL and NoSQL databases
- Experience working with Linux, shell scripting
- Previous startup experience strongly preferred
Bonus Points
- Experience implementing applications on Google Cloud Platform
- Experience with deep generative models or graph learning a plus.
- Tag your application with your solution to an active / recently concluded Kaggle competition, to get ahead of the list :)
- Experience leading a team of data and data scientists; Strong ability to multiply the effect of the team and the team members; excellent written communication; self-starter that can balance sophistication with practicality
Why Narvar?
We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!
From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ + other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.
Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.
We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
#LI-BB1
#LI-Remote
The range reflects the minimum and maximum target for new hire salaries for the position across the US. Within the range, individual compensation packages are based on factors unique to each candidate, including but not limited to, skill set, education and certifications, and work location.
Please read our Privacy Policy to learn what personal information we collect in connection with your job application, and how we may use and share it.
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Senior Software Engineer II
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SurveyMonkey is the world’s most popular platform for surveys and forms, built for business—loved by users. We combine powerful capabilities with intuitive design, effectively serving every use case, from customer experience to employee engagement, market research to payment and registration forms. With built-in research expertise and AI-powered technology, it’s like having a team of expert researchers at your fingertips.
Trusted by millions—from startups to Fortune 500 companies—SurveyMonkey helps teams gather insights and information that inspire better decisions, create experiences people love, and drive business growth. Discover how at surveymonkey.com.
What we’re looking for
The Machine Learning Platform team (MLP) is seeking a Senior Software Engineer II to design and implement the secure, highly scalable, and high-performance pipelines that govern the end-to-end lifecycle of ML models.
You will work at the intersection of Data Science and DevOps, building the "connective tissue" that empowers our product portfolio to leverage technologies like Generative AI, Natural Language Processing (NLP), and real-time classification. We are looking for a subject matter expert who will drive innovation and deliver results that meet the dynamic needs of a high-growth AI environment. You will report to the Senior Engineering Manager on the MLP Solutions team.
What you’ll be working on
- Build and maintain robust ML systems using Python (Pandas/NumPy, PyTorch/transformers) to support efficient ML operations.
- Design ML cloud infrastructure using AWS services, ensuring the platform is built for reuse, scalability, and high-volume throughput.
- Collaborate with application engineers to integrate, test, and monitor ML model services across SurveyMonkey’s microservices architecture.
- Act as a consultant to internal feature teams, educating and influencing decisions regarding ML tooling and infrastructure.
- Incorporate telemetry into the platform for complex failure mode analysis, ensuring real-time reliability for millions of daily survey responses.
- Serve as a technical leader and mentor, championing high standards in coding, documentation, and architectural best practices to foster the professional growth of junior engineers on the MLP team.
We’d love to hear from people with
- 8+ years of professional ML development experience with a proven track record of designing and implementing ML infrastructure in AWS.
- Mastery of ML concepts (supervised/unsupervised learning) and deep understanding of Large Language Models (LLMs) and NLP.
- Expert-level Python skills and experience with high-scale data processing (PySpark, etc.).
- Comfortable with Unix/Linux systems and experienced in deploying end-to-end solutions for real-time applications (spam detection, personalization, ranking).
- Bachelor’s Degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.
The base pay provided for this position ranges from CAD $126,400.00/ year - $158,000.00/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.
Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits.
This opening is for an existing vacancy.
SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution in problem-solving and decision-making. As such, you will be required to work from our Ottawa office up to 1 day per week.
#LI-Hybrid
Why SurveyMonkey? We’re glad you asked
At SurveyMonkey, curiosity powers everything we do. We’re a global company where people from all backgrounds can make an impact, build meaningful connections, and grow their careers. Our teams work in a flexible, hybrid environment with thoughtfully designed offices and programs like the CHOICE Fund to help employees thrive in work and life.
We’ve been trusted by organizations for over 25 years, and we’re just getting started. Our milestones include celebrating a quarter-century of curiosity with 25 acts of giving, opening new hubs in Costa Rica and India, crossing the threshold of 100 billion questions answered, and earning recognition as one of the Most Inspiring Workplaces across North America and Asia.
We live our company values—like championing inclusion and making it happen—by embedding them into how we hire, collaborate, and grow. They help shape everything from our culture to our business decisions. Come join us and see where your curiosity can take you.
Our commitment to an inclusive workplace
SurveyMonkey is an equal opportunity employer committed to providing a workplace free from harassment and discrimination. We celebrate the unique differences of our employees because that is what drives curiosity, innovation, and the success of our business. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate. Accommodations are available for applicants with disabilities.
Your data
For more information on how SurveyMonkey (including its subsidiary and affiliated companies) processes your personal data as a job candidate or applicant, please see our Global Applicant and Candidate Data Privacy Notice. Please note that we may use artificial intelligence (AI) tools to support parts of the hiring process, such as sourcing candidates, reviewing applications, analyzing resumes, or summarizing interviews. These tools assist our recruitment team but do not replace human judgment.
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Apply to SurveyMonkeyLevel Up Your Career with Zynga!
At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition.
From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more!
Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level.
Join us and be part of the play!
Position Overview:
Come join the team at Zynga making an impact across all of the company’s games - Mobile Game Tech! Do you love developing data models and visualizations to help teams make strategic decisions? This analyst role is a key figure in our cost transparency efforts on the FinOps team, delivering critical insights into service costs. This position also provides dashboards, data visualizations, and analyses for areas that make our org effective at serving our internal customers, allowing all teams to make better decisions.
What You'll Do:
- Lead financial analysis activities with regards to internal cost allocations for technology spend
- Lead data model design and data analysis aspects of the FinOps team’s software development, including close collaboration with other FinOps software engineers
- Engage with customers and stakeholders to design and iterate upon user-facing data visualizations
- Develop data ingestion and normalization to serve data visualizations and dashboards, as well as owning maintenance and ensuring ongoing data quality
- Support FinOps guidelines and work with other teams and partners to implement cost analysis and optimizations for technology spend across Zynga
- Interact with members of Finance and the C-suite with regards to technology cost allocations, forecasts, and ad hoc FinOps-related requests
What You Bring:
- B.S. in Computer Science, Math, Statistics, Engineering, or other quantitative field (or equivalent experience)
- Demonstrated proficiency with Python for data cleaning and data wrangling (pandas, NumPy), and ability to work with source code via pull requests, CICD pipelines, etc
- 8+ years of hands-on experience with the following: SQL, data warehouses, Tableau or similar data visualization tools
- Ability to design monitoring rules for validating data quality within data pipelines
- Experience collaborating with customers to assess their analysis and visualization needs and design solutions that present the data effectively and clearly
- Ability to think through the UI/UX of data visualizations to best serve the target audience's needs
- Comfort interacting with stakeholders at a much more senior level, ability to adjust communication style to the audience
- Experience working autonomously and capable of tackling solo projects with ease
Bonus Points:
- Familiarity with FinOps practices
- Familiarity with financial concepts related to budgeting, forecasts, amortization, etc
- Previous experience with software engineering platforms such as AWS, Splunk, Datadog
What We Offer You:
Zynga offers a world-class benefits package that helps support and balance the needs of our teams. To find out more about our benefits, visit the Zynga Benefits site.
The pay range for this position in Ontario at the start of employment is expected to be between $119,140 and $169,140 per year. However, base pay offered is based on market location, and may vary further depending on individualized factors for job candidates, such as job-related knowledge, skills, experience, and other objective business considerations.
Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards and eligibility to participate in our 401(K) plan and Employee Stock Purchase Program. Regular, full-time employees are also eligible for a range of benefits at the Company, including: medical, dental, vision, and basic life insurance coverage; 14 paid holidays per calendar year; paid vacation time per calendar year (ranging from 15 to 25 days) or eligibility to participate in the Company’s discretionary time off program; up to 10 paid sick days per calendar year; paid parental and compassionate leave; wellbeing programs for mental health and other wellness support; family planning support through Maven; commuter benefits; and reimbursements for fitness-related expenses. The use of Artificial Intelligence is not being used to screen candidates. The position is for an existing vacancy.
We are proud to be an equal opportunity employer, which means we are committed to creating and celebrating diverse thoughts, cultures, and backgrounds throughout our organization. Employment with us is based on substantive ability, objective qualifications, and work ethic – not an individual’s race, creed, color, religion, sex or gender, gender identity or expression, sexual orientation, national origin or ancestry, alienage or citizenship status, physical or mental disability, pregnancy, age, genetic information, veteran status, marital status, status as a victim of domestic violence or sex offenses, reproductive health decision, or any other characteristics protected by applicable law.
As an equal opportunity employer, we are committed to providing the necessary support and accommodation to qualified individuals with disabilities, health conditions, or impairments (subject to any local qualifying requirements) to ensure their full participation in the job application or interview process. Please contact us at accommodationrequest@zynga.com to request any accommodations or for support related to your application for an open position.
Please be aware that Zynga does not conduct job interviews or make job offers over third-party messaging apps such as Telegram, WhatsApp, or others. Zynga also does not engage in any financial exchanges during the recruitment or onboarding process, and will never ask a candidate for their personal or financial information over an app or other unofficial chat channel. Any attempt to do so may be the result of a scamp or phishing attack, and you should not engage. Zynga’s in-house recruitment team will only contact individuals through their official Company email addresses (i.e., via a zynga.com, take2games.com, naturalmotion.com, smallgiantgames.com, themavens.com, gram.gs email domain).
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Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between.
At Caylent, our people always come first. We are a global company and operate fully remote with employees in Canada, the United States, and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien!
The Mission
We are seeking a highly experienced and skilled Principal Data Architect to join our Cloud Data Engineering Practice. The Principal Data Architect will be responsible for leading the design and implementation of complex cloud-based data solutions for our customers. The ideal candidate will have a deep understanding of cloud data and analytics technologies.
Your Assignment
- Define strategic roadmaps and targeted outcomes for our clients in a consultative capacity
- Act as a data engineering SME to define upcoming engagements working with our pre-sales teams
- Perform technical interviews for Architect and Engineer candidates as well as provide technical guidance to Architects and Engineers
- Oversee the development and implementation of data standards and operating procedures
Requirements
- At least 4 years of experience in AWS data landscape
- 10 years of experience designing and building complex data systems as well as experience in these areas:
- Traditional Data (At least 2):
- Relational database design, optimization and migration
- Data modeling for both transactional and analytics systems including implementation of industry standard data models
- BI dashboards and visualizations
- Data Governance and MDM
- New Data (at least 2):
- Big data processing using Spark, Streaming solutions, and NoSQL
- Machine Learning and MLOps with proficiency in Sagemaker
- GenAI Foundational Models as well as approaches and frameworks used in conjunction with them with proficiency in Bedrock.
- DataOps practices (Infrastructure as Code, Data Testing, Data Versioning,etc)
- Traditional Data (At least 2):
- Experience with at least two of these:
- Infrastructure as Code tools
- CI/CD pipelines and tools
- Python for analytics (numpy, pandas, matplotlib etc) and automation
- Strong drive towards standardizing and documenting our approach and solutions
- Excellent written and verbal communication skills
Benefits
- 100% remote work
- Equitable Life - Hybrid Plan
- 100% Premium Coverage for the employee and dependents
- Competitive phantom equity
- Long-Term Disability
- 4% Pension match (employer contribution)
- Unlimited Vacations
- Sick Leave
- Paid Holidays
- Parental Leave
- Paid for exams and certifications
- Peer bonus awards
- State of the art laptop and tools
- Equipment & Office Stipend
- Individual professional development plan
- Annual stipend for Learning and Development
- Work with an amazing worldwide team and in an incredible corporate culture
Base Salary Range: The expected base salary range for this position is CAD $180,000 - $223,000 per year, commensurate with experience and qualifications.
Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.
This role may require up to 25% travel, depending on business needs.
NOTE: We’re unable to provide visa sponsorship now or at any time in the future.
At Caylent, we are committed to fair, transparent, and inclusive hiring practices. As part of our recruitment process, we may use artificial intelligence (AI) tools or automated systems to assist with the screening and evaluation of applications to help match candidate qualifications with job requirements.
These tools are designed to support — not replace — human decision-making. Final hiring decisions are always made by our trained recruitment professionals.
If an AI or automated tool is used during your application process, it will only be in accordance with applicable laws and regulations, and your information will be handled in a secure and confidential manner.
If you have any questions, please contact talent@caylent.com
Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.
We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.Ready to apply?
Apply to CaylentAbout the role:
At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable. This role will involve hands-on work on cutting-edge projects, requiring innovative and passionate machine learning engineers who can bring research into practical, scalable applications.
As a Machine Learning Engineer, your goal will be to take AI Agents from the realm of research and bring them into practical, real-world use cases. This includes developing and deploying proprietary LLMs, scaling AI solutions, and addressing key challenges such as evaluation and reliability. While we’re focused on real-world application rather than pure research, you’ll be working with some of the most advanced technologies in the GenAI space.Responsibilities:
- Design, develop, and deploy Cresta’s AI Agent solutions and proprietary models.
- Focus on practical AI challenges such as improving reasoning, planning capabilities, and evaluation in real-world scenarios.
- Collaborate with cross-functional teams including front-end and back-end software engineers to integrate AI Agents into Cresta’s customer solutions.
- Lead initiatives to scale AI systems for production environments, ensuring performance and reliability across use cases.
- Contribute to solving cutting-edge problems in AI and help define the future roadmap for Cresta’s AI Agents.
- Innovate and research ways to improve security, cost-efficiency, and reliability of AI systems.
Qualifications We Value:
- Bachelor’s or Master's Degree in Computer Science, Mathematics, or a related field
- 2+ years of hands-on industry experience with AI and machine learning, preferably with experience working with LLMs in large-scale production environments
- Solid knowledge of machine learning concepts and methods, especially those related to NLP, Generative AI, and working with LLMs
- Practical knowledge of modern machine learning frameworks and technologies (e.g., PyTorch, Tensorflow, Hugging Face, NumPy), as well as experience with distributed systems and cloud-based AI infrastructure
- Strong problem-solving and strategic thinking abilities, with a proven ability to lead cross-functional teams and work collaboratively to deliver innovative AI solutions in production
- A passion for driving AI adoption and pushing the boundaries of AI technology into real-world applications, with an ability to mentor junior engineers and influence strategic decisions across the organization
Perks & Benefits:
- We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs
- Paid parental leave to support you and your family
- Monthly Health & Wellness allowance
- Work from home office stipend to help you succeed in a remote environment
- Lunch reimbursement for in-office employees
- PTO: 3 weeks in Canada
Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details.
We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai
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Senior Data Scientist, Menu Personalization
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The role
Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you!
You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh’s global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production.
To succeed in this role you should be curious, able to deal with uncertainty, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally.
What you’ll do
- Join and become an integral part of a high-impact team covering menu personalization.
- Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.
- Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.
- Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
- Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.
- Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.
- Analyze the performance of our models to understand customer behavior, and come up with improvements.
- Contribute to a collaborative and knowledge-sharing environment.
What you’ll bring
- Proven track record of scientific work in your Bachelor's, Master's, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.
- Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
- In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.
- Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).
- Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.
- Experience with software development practices and tools (Git, CI/CD, Docker, AWS).
- You love to learn, are a critical thinker and creative problem solver who strives for excellence.
- You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.
- Exceptional communication and collaboration capabilities.
- Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.
Interacting with product managers, UX designers, data and backend engineers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders.
Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills, and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.
Let’s cut to the cheese, this is why you'll love it here
- Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
- Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
- Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance.
- Family Benefits - A parental leave top-up program for expectant parents.
- Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
- Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
- Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
- Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!
Flexible Hybrid Approach
At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience.
To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.
#LI-HYBRID
HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.
This is a posting for an existing vacancy. We are actively seeking to fill this position.
#DATA
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Senior Software Engineer - Python and Data Ecosystem
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About ClickHouse
Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.
The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.
We’re on a mission to transform how companies use data. Come be a part of our journey!
The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.
Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.
About the role
As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.
We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.
You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:
- Orchestration Platforms: Apache Airflow, Dagster, Prefect
- Transformation Tools: dbt, SQLMesh
- AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications
ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real: building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.
What you'll do
- Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
- Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
- Drive the AI/LLM integration strategy: designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
- Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
- Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
- Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows
About you
- 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
- Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
- Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
- Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
- Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
- Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
- Solid experience with concurrent Python: threading, multiprocessing, and async patterns
- Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities
Bonus points for:
- Experience deploying AI/ML models in production, including inference APIs and vector databases
- Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
- Familiarity with ClickHouse or similar high-performance OLAP platforms
- Familiarity with the JVM ecosystem
Compensation
For roles based in the United States, the typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed.
These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments.
An individual’s placement within the range will depend on various factors, including (but not limited to) education, qualifications, certifications, experience, skills, location, performance, and the needs of the business or organization.
If you have any questions or comments about compensation as a candidate, please get in touch with us at paytransparency@clickhouse.com.
Perks
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 20 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new team member who joins our company receives stock options.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A $500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
Culture - We All Shape It
As part of a rapidly scaling start up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here. Check out our blog posts or follow us on LinkedIn to find out more about what’s happening at ClickHouse.
Equal Opportunity & Privacy
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here for our Privacy Statement.
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Software Engineer, ML Platform
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Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
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
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
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Junior Data Scientist
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Junior Data Scientist
The Wiley Edge banking team is currently seeking a Data Scientist to work across the Front Office Trading, Risk & Regulatory Compliance Trade Analytics group, using Machine Learning and Data Analytics techniques to design and develop complex data models for client and trading analytics across their Fixed Income and FX offerings.
You will be supporting the transformation from traditional controls monitoring to “on-screen” data driven monitoring and analytical solutions.
Tools:
- Python (pandas, numpy)
- Machine Learning Algorithms / Natural Language Processing (NLP)
- AI / Robotics
- Predictive Analysis
- Good grasp of ML Algorithms
Starting Salary: CA$85,000 per annum
Junior Data Scientist
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Sr. AI/ML Engineer
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Role Summary
As a Senior AI/ML Engineer, you will lead the design and deployment of high-impact AI solutions, expertly bridging traditional predictive modeling with next-generation Agentic AI. You are equally comfortable tuning a Gradient Boosted Tree for structured data as you are architecting a multi-agent system for complex reasoning tasks. You will collaborate directly with clients to understand their needs, translate business challenges into technical solutions, and provide expert guidance on AI/ML best practices. The role requires overseeing dataset quality for model training and leveraging GCP for efficient model deployment and scaling. You will utilize the Google AI ecosystem (Vertex AI, Google ADK) and orchestration frameworks like LangChain/LangGraph to move AI solutions from experimental demos to reliable, production-grade systems grounded in statistical rigor.
Role and Responsibility
- Architect and implement sophisticated multi-agent systems and autonomous workflows leveraging the Google AI SDK, LangGraph, and LangChain to solve complex, non-linear business processes.
- Lead the design and construction of cloud-native solutions, using Terraform, Kubernetes, and Docker to ensure that AI models are deployed on scalable, reliable infrastructure.
- Apply rigorous statistical evaluation frameworks to model performance, moving beyond standard metrics to include uncertainty estimation, calibration, and robust hypothesis testing during model optimization (LoRA, QLoRA).
- Lead the development of custom predictive models and deep learning solutions, utilizing frameworks like PyTorch and Scikit-Learn to select suitable architectures—whether decision trees, neural nets, or ensembles—based on performance and client criteria.
- Design and implement state-of-the-art generative models for NLP and multimodal tasks, leveraging tools like OpenCV for image preprocessing and Stable Diffusion concepts where applicable.
- Champion MLOps best practices within the team, building validated data pipelines and CI/CD/CT workflows using Kubeflow and Vertex AI Pipelines to ensure model quality and integrity.
- Collaborate directly with clients to understand their unique needs, translating business challenges into technical solutions and providing expert guidance on dataset management best practices.
- Personally tackle the most difficult engineering challenges, identifying technical risks such as overfitting or latency issues, and optimizing hyperparameters to ensure precision and interpretability.
Required Experience and Qualifications
- 7+ years of technical experience, with at least 3+ years focused on ML/AI and 1 year in a consulting capacity.
- Experience building and evaluating agentic loops, including tool-use (function calling), self-reflection, and multi-step reasoning architectures.
- Deep proficiency in the modern Python AI stack, including extensive experience with core libraries (NumPy, Pandas, PyTorch) and specialized LLMOps/Agentic tools for monitoring and evaluation (e.g., LangSmith, Braintrust, AgentOps, or HoneyHive)
- Proven track record of building AI/ML solutions for users, including experience with GenAI common solutions like Vertex AI, OpenAI API, and vector database technologies.
- Strong foundation in probabilistic modeling, Bayesian statistics, and experimental design (A/B testing for AI) to ensure model reliability and groundedness.
- Excellent verbal and written communication skills, with the ability to confidently articulate complex AI concepts to business, technical, and non-technical stakeholders.
Education/Certifications
- Google Cloud: Professional Machine Learning Engineer
- Industry: Databricks Certified Machine Learning Professional OR DeepLearning.AI Generative AI Specialization.
- Education in: Computer Science, Mathematics, Machine Learning/Data Science
What We Offer
- Competitive Compensation – Market-aligned salary reflecting your expertise and impact
- Remote Work Flexibility – Work in a remote first organization, but can still collaborate at multiple offices globally.
- Comprehensive Health Benefits – Medical, dental, vision, and wellness coverage for you and your family.
- Flexible Paid Time Off – Take the time you need with a results-focused approach
- Professional Development – Work with industry leaders, and learn from the most talented engineers in the industry.
- Google Cloud Training & Certifications – Access to leading cloud education resources.
- High-Impact Client Work – Enterprise engagements shaping the future of Cloud, Data Platforms, and Agents
- Collaborative Culture – Professional, transparent, and team-oriented environment.
Our Diversity and Inclusion Commitment
At CloudWerx, we are dedicated to creating a workplace that values and celebrates diversity. We believe that a diverse and inclusive environment fosters innovation, collaboration, and mutual respect. We are committed to providing equal employment opportunities for all individuals, regardless of background, and actively promote diversity across all levels of our organization. We welcome all walks of life, as we are committed to building a team that embraces and mirrors a wide range of perspectives and identities. Join us in our journey toward a more inclusive and equitable workplace.
Background Check Requirement
All candidates for employment will be subject to pre-employment background screening for this position. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process, please reach out to us directly.
Our Story
CloudWerx is an engineering-focused cloud consulting firm born in Silicon Valley - in the heart of hyper-scale and innovative technology. In a cloud environment we help businesses looking to architect, migrate, optimize, secure or cut costs. Our team has unique experience working in some of the most complex cloud environments at scale and can help businesses accelerate with confidence.
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