Machine Learning Engineer

FloVision Solutions

Machine Learning Engineer building production computer vision and deep learning systems for FloVision’s food-processing automation. Improving data quality, model deployment, and food-supply-chain sustainability remotely in the U.S.

Posted 8/18/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $90,000 - $115,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing computer vision models and deep learning capabilities, with strong proficiency in Python and experience in the machine learning lifecycle. Capable of building high-quality datasets, performing statistical analysis, and deploying models in production environments.

Highest-signal resume keywords

Computer VisionDeep LearningPython ProgrammingMLOps PracticesStatistical Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnnotationFeature EngineeringSemantic SegmentationETL PipelinesModel EvaluationData IntegrityModel DeploymentStatistical AnalysisData Collection

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration SkillsAdaptability

Tools & Technologies

PyTorchTensorFlowJupyterPandasNumPyMatplotlibAWSGCPAzureAI-Assisted Development Tools

Industry Keywords

Machine Learning LifecycleData ScienceProduction EnvironmentsData QualityCross-Functional Teamwork

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformNumpyPandasPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

Design, develop, and optimize computer vision models and deep learning capabilities across the product portfolio
Contribute to projects across the company in collaboration with machine learning, software, hardware, product, and data annotation teams
Work across the machine learning lifecycle, from data collection and annotation through experimentation, development, deployment, and monitoring
Build high-quality datasets, strengthen data integrity, validate model results, and ensure production impact
Build and maintain ETL pipelines for structured and unstructured machine learning data
Clean datasets and perform feature engineering
Annotate and review image data throughout the machine learning workflow
Use Python, SQL, and statistical analysis to explore data and identify actionable insights
Train, fine-tune, evaluate, and experiment with deep learning models for computer vision
Own machine learning outcomes from data quality and model performance through deployment and product impact
Improve data quality, labeling practices, and machine learning workflows with the annotation team
Productionize, deploy, and monitor models with machine learning and software engineering teams
Make machine learning processes and results accessible across the company
Make independent technical decisions and drive projects forward autonomously

Requirements

What you’ll need

Bachelor’s degree in computer science, engineering, mathematics, or a related field, or equivalent practical experience
Three or more years of experience across the machine learning or data science lifecycle, focused on computer vision
Experience applying semantic segmentation to a real-world business or production use case
Strong Python programming skills
Experience with PyTorch or TensorFlow, Jupyter, pandas, NumPy, and Matplotlib
Experience using AI-assisted development tools to improve productivity, quality, and speed
Experience performing statistical analysis and rigorously evaluating machine learning models
At least two years of experience with a major cloud platform such as AWS, GCP, or Azure
Working knowledge of MLOps practices and principles for deploying, monitoring, and maintaining reliable production machine learning systems
Strong analytical, programming, and problem-solving skills
Ability to work in a fast-paced startup environment, iterate quickly, and balance speed with quality standards
Strong communication and collaboration skills for cross-functional teamwork
Ability to work U.S. Central working hours
Comfortable working in active production environments that may be greasy, loud, cold, and physically demanding
Willingness to travel up to 10% of the time, including domestic travel and occasional international travel
Submission of a short 1–2 minute introductory video; applications without a video will not be considered

Benefits

Comp & perks

Home Office Stipend
Medical Insurance
Dental Insurance
Vision Insurance
401(k) Plan
Health Savings Account (HSA)
Comp days when weekend travel is required
Flexible work hours
Flexible work arrangements
Growth opportunities
In-person collaboration opportunities