Machine Learning Engineer at Fortune Brands Innovations in Deerfield, IL | USD105,000-165,000 | Kablio

Role

Description

kubernetes

tensorflow

training pipelines

model monitoring

data preprocessing

api integration

Maintain and optimize existing ML inference services deployed in Kubernetes.
Develop and enhance TensorFlow-based image classification models.
Collaborate with Engineers to ensure seamless integration between machine learning components and API services.
Implement feedback loops utilizing corrections from subject matter experts and metrics.
Design and implement training pipelines for model iteration and improvement.
Work with full-stack engineers to integrate ML components into the broader application.
Prototype and implement new features leveraging machine learning capabilities.
Monitor model performance in production and implement strategies to handle data drift.
Partner with subject matter experts to understand domain-specific challenges.
Research state-of-the-art computer vision techniques applicable to image recognition.
Document ML approaches, model versions, and performance metrics.
Evaluate new approaches for improving identification accuracy and processing efficiency.
Develop data preprocessing pipelines for image normalization and augmentation.
Analyze model performance and implement techniques to improve accuracy and reduce false positives.
Work with labeled datasets from the review interface to improve model quality.

Requirements

python

tensorflow

docker

kubernetes

azure

computer vision

Experience with image recognition or similar identification systems.
Knowledge of image processing techniques and computer vision algorithms.
3+ years of experience in developing and deploying machine learning models.
Experience building and maintaining web-enabled AI solutions including front-end and back-end development hosted in the Azure
Familiarity with SQL or similar databases for storing model outputs and metadata.
Background in developing systems that incorporate human feedback for model improvement.
Experience developing AI agents and MCP Servers
Understanding of ML model versioning, monitoring, and maintenance.
Experience with containerized ML deployments (Docker, Kubernetes).
Familiarity with REST APIs and microservices architectures.
Experience with CI/CD pipelines for ML model deployment.
REACT development skills are a nice to have
Strong background in computer vision and image classification.
Master's or Bachelor's degree in Computer Science, Machine Learning, or related field.
Proficiency in Python and machine learning frameworks (TensorFlow required, ONNX or PyTorch a plus).

Benefits

Information not given or found

Training + Development

Information not given or found

Interview process

Information not given or found

Visa Sponsorship

Information not given or found

Security clearance

Information not given or found

Company

Overview

A leader in innovation, transforming everyday spaces with smart, functional products.
Focused on creating sustainable solutions that enhance the way people live, work, and play.
With decades of experience, the company has pioneered advancements in home hardware, kitchen, and bath industries.
Their product lines include iconic brands that redefine comfort, performance, and design.
From high-end kitchen systems to innovative home security technologies, Fortune Brands is at the forefront of next-gen solutions.
Known for its strong financial growth, the company continues to expand its reach globally with cutting-edge designs.
They have a history of pushing boundaries with both traditional and digital product offerings.

Culture + Values

Purpose: "We Elevate Every Life by Transforming Spaces into Havens."
Blueprint Behaviors: "Think Big, Learn Fast; Work It Together; Make the Hard Call."
Strategic Drivers: "Brands that Create Impact; Partner that Sets the Pace; Ecosystems that Change the Game; Fuel that Powers our Purpose."
High standards: core values include integrity and accountability (from Code of Business Conduct and Ethics).
Operating model focus areas: category management, global supply chain excellence, business simplification, digital transformation.

Environment + Sustainability

30% by 2030

Carbon Emissions Reduction

Aims to reduce Scope 1 & 2 carbon emissions by 30% from 2022 baseline by 2030.

50% by 2030

Renewable Energy Offset

Target to offset 50% of electricity usage with renewable sources by 2030.

1.4m kWh

On-Site Solar Generation

Generated 1.4 million kWh of solar energy in 2023 across three sites, with one more site expected by 2025.

1 Trillion Gallons

Water Conservation Goal

Aimed to save 1 trillion gallons of water by 2030; achieved ~257 billion gallons by 2023.

2,000 Tons

Ocean Plastic Repurposed

Target to repurpose 2,000 tons of ocean plastic by 2030; achieved ~750 tons by 2023.

Signed virtual power purchase agreement for 60 MW solar in CA, starting early 2028, covering ~68% of 2023 electricity usage.
Fiberon PE composite decking contains ≥94% recycled mixed wood fiber and plastic; recycles ~100 million lbs of plastic annually.
Therma‑Tru doors are ENERGY STAR qualified and designed for energy conservation.
Global TRIR safety record: <1.0 in 2023 (ex‑acquisitions).

Inclusion & Diversity

60% associates

Hourly Production Roles

60% of associates work in hourly production roles, reflecting equitable employment opportunities.

TRIR <1.0

Global Safety Metric

The company maintains a global Total Recordable Incident Rate (TRIR) below 1.0, demonstrating a commitment to a safe and inclusive work environment.

2021 DEI Strategy

Comprehensive Equity Initiative

A comprehensive diversity, equity, and inclusion (DEI) strategy was launched in 2021, informed by global employee engagement surveys and actionable outcomes.

First ESG-linked Goals

2021 Implementation

The company introduced its first environmental, social, and governance (ESG)-linked DEI goals in 2021, emphasizing transparency and accountability in diversity and inclusion efforts.

Associate Resource Groups (ERGs) support inclusivity and authentic self-expression.
Women representation: Board composition above benchmark for manufacturing companies (as of May 7, 2024).

Articles

Careers

Press Releases

Investor FAQs

Role

Description

kubernetes

tensorflow

training pipelines

model monitoring

data preprocessing

api integration

Maintain and optimize existing ML inference services deployed in Kubernetes.
Develop and enhance TensorFlow-based image classification models.
Collaborate with Engineers to ensure seamless integration between machine learning components and API services.
Implement feedback loops utilizing corrections from subject matter experts and metrics.
Design and implement training pipelines for model iteration and improvement.
Work with full-stack engineers to integrate ML components into the broader application.
Prototype and implement new features leveraging machine learning capabilities.
Monitor model performance in production and implement strategies to handle data drift.
Partner with subject matter experts to understand domain-specific challenges.
Research state-of-the-art computer vision techniques applicable to image recognition.
Document ML approaches, model versions, and performance metrics.
Evaluate new approaches for improving identification accuracy and processing efficiency.
Develop data preprocessing pipelines for image normalization and augmentation.
Analyze model performance and implement techniques to improve accuracy and reduce false positives.
Work with labeled datasets from the review interface to improve model quality.

Requirements

python

tensorflow

docker

kubernetes

azure

computer vision

Experience with image recognition or similar identification systems.
Knowledge of image processing techniques and computer vision algorithms.
3+ years of experience in developing and deploying machine learning models.
Experience building and maintaining web-enabled AI solutions including front-end and back-end development hosted in the Azure
Familiarity with SQL or similar databases for storing model outputs and metadata.
Background in developing systems that incorporate human feedback for model improvement.
Experience developing AI agents and MCP Servers
Understanding of ML model versioning, monitoring, and maintenance.
Experience with containerized ML deployments (Docker, Kubernetes).
Familiarity with REST APIs and microservices architectures.
Experience with CI/CD pipelines for ML model deployment.
REACT development skills are a nice to have
Strong background in computer vision and image classification.
Master's or Bachelor's degree in Computer Science, Machine Learning, or related field.
Proficiency in Python and machine learning frameworks (TensorFlow required, ONNX or PyTorch a plus).

Benefits

Information not given or found

Training + Development

Information not given or found

Interview process

Information not given or found

Visa Sponsorship

Information not given or found

Security clearance

Information not given or found

Company

Overview

A leader in innovation, transforming everyday spaces with smart, functional products.
Focused on creating sustainable solutions that enhance the way people live, work, and play.
With decades of experience, the company has pioneered advancements in home hardware, kitchen, and bath industries.
Their product lines include iconic brands that redefine comfort, performance, and design.
From high-end kitchen systems to innovative home security technologies, Fortune Brands is at the forefront of next-gen solutions.
Known for its strong financial growth, the company continues to expand its reach globally with cutting-edge designs.
They have a history of pushing boundaries with both traditional and digital product offerings.

Culture + Values

Purpose: "We Elevate Every Life by Transforming Spaces into Havens."
Blueprint Behaviors: "Think Big, Learn Fast; Work It Together; Make the Hard Call."
Strategic Drivers: "Brands that Create Impact; Partner that Sets the Pace; Ecosystems that Change the Game; Fuel that Powers our Purpose."
High standards: core values include integrity and accountability (from Code of Business Conduct and Ethics).
Operating model focus areas: category management, global supply chain excellence, business simplification, digital transformation.

Environment + Sustainability

30% by 2030

Carbon Emissions Reduction

Aims to reduce Scope 1 & 2 carbon emissions by 30% from 2022 baseline by 2030.

50% by 2030

Renewable Energy Offset

Target to offset 50% of electricity usage with renewable sources by 2030.

1.4m kWh

On-Site Solar Generation

Generated 1.4 million kWh of solar energy in 2023 across three sites, with one more site expected by 2025.

1 Trillion Gallons

Water Conservation Goal

Aimed to save 1 trillion gallons of water by 2030; achieved ~257 billion gallons by 2023.

2,000 Tons

Ocean Plastic Repurposed

Target to repurpose 2,000 tons of ocean plastic by 2030; achieved ~750 tons by 2023.

Signed virtual power purchase agreement for 60 MW solar in CA, starting early 2028, covering ~68% of 2023 electricity usage.
Fiberon PE composite decking contains ≥94% recycled mixed wood fiber and plastic; recycles ~100 million lbs of plastic annually.
Therma‑Tru doors are ENERGY STAR qualified and designed for energy conservation.
Global TRIR safety record: <1.0 in 2023 (ex‑acquisitions).

Inclusion & Diversity

60% associates

Hourly Production Roles

60% of associates work in hourly production roles, reflecting equitable employment opportunities.

TRIR <1.0

Global Safety Metric

The company maintains a global Total Recordable Incident Rate (TRIR) below 1.0, demonstrating a commitment to a safe and inclusive work environment.

2021 DEI Strategy

Comprehensive Equity Initiative

A comprehensive diversity, equity, and inclusion (DEI) strategy was launched in 2021, informed by global employee engagement surveys and actionable outcomes.

First ESG-linked Goals

2021 Implementation

The company introduced its first environmental, social, and governance (ESG)-linked DEI goals in 2021, emphasizing transparency and accountability in diversity and inclusion efforts.

Associate Resource Groups (ERGs) support inclusivity and authentic self-expression.
Women representation: Board composition above benchmark for manufacturing companies (as of May 7, 2024).

Articles

Careers

Press Releases

Investor FAQs