[Remote] Staff ML Platform Engineer at Afresh

Ontario, Canada

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Food Tech, Grocery Retail, AIIndustries

Requirements

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
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 Python

Responsibilities

Deliver projects in the first 3 months, such as generalizing model configuration, enabling no-code model deploys for various ML solutions, or improving integration testing across ML systems
By the end of the first 6 months, own the design and implementation of significant scalability improvements and additions to the ML platform, such as new feature pipelines for the recommendation engine or standing up real-time inference
Build and maintain foundational infrastructure and tooling for machine learning and applied science solutions, including performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, scalable training pipelines, and deep experimentation capabilities
Elevate the core ML platform to improve performance, reliability, and scalability to support growing product suite and customer base, accommodating predictions and simulations across various time scales, complex data hierarchies, and configuration possibilities

Skills

Key technologies and capabilities for this role

Machine LearningML PlatformData APIFeaturizationForecasting SystemsOptimization EnginesTraining PipelinesExperimentationScalabilityInfrastructurePythonKubernetesDockerAWSDistributed Systems

Questions & Answers

Common questions about this position

What education and experience are required for this Staff ML Platform Engineer role?

A BS in Computer Science or relevant technical field is required, along with 7+ years of professional software development experience and a proven track record of shipping high-quality applications and services.

What salary or compensation does this position offer?

This information is not specified in the job description.

Is this ML Platform Engineer role remote or does it require office work?

This information is not specified in the job description.

What will I be working on in the first few months as a Staff ML Platform Engineer?

In the first 3 months, you might deliver projects like generalizing model configuration, enabling no-code model deploys, or improving integration testing; by 6 months, you'll own scalability improvements such as new feature pipelines or real-time inference.

What kind of collaboration is expected in this role?

You will work collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale projects.

Afresh

AI solutions for fresh food inventory management

About Afresh

Afresh Technologies provides solutions for grocery retailers to improve their inventory management in the fresh food supply chain. Their platform uses machine learning algorithms to help retailers reduce food waste and increase profitability by optimizing how they manage their stock. Retailers subscribe to Afresh's service, gaining access to its features and potentially additional services like data analytics and consulting. What sets Afresh apart from competitors is its specific focus on the fresh food sector and its commitment to helping retailers meet consumer demand while minimizing waste. The company's goal is to enhance the efficiency of fresh food management in retail.

33 New Montgomery St, San Francisco, CA 94105, USAHeadquarters

2017Year Founded

$147.8MTotal Funding

SERIES_BCompany Stage

Food & Agriculture, Enterprise Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Comprehensive health plans

Competitive compensation

Generous parental leave

Equity packages

401(k) matching

Flexible vacation policy

Monthly grocery stipend

Professional development program

Risks

Tech giants entering AI supply chain space threaten Afresh's market share.

AI advancements may render Afresh's platform obsolete if not updated.

Data privacy regulations could hinder Afresh's data collection and usage.

Differentiation

Afresh uses AI to optimize fresh produce inventory management for retailers.

The platform minimizes waste and maximizes freshness through advanced machine learning.

Afresh offers a subscription model, providing continuous access to its AI-driven solutions.

Upsides

Growing demand for AI in supply chain boosts Afresh's market potential.

Retailers seek sustainable solutions, aligning with Afresh's waste-reduction mission.

Omnichannel retailing increases need for sophisticated inventory systems like Afresh's.

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