[Remote] Machine Learning Engineer
Note: The job is a remote job and is open to candidates in USA. FloVision is a remote-first startup focused on improving the food supply chain through computer vision and machine learning-assisted production processes. The Machine Learning Engineer will design, develop, optimize, deploy, and monitor computer vision and deep learning models while managing data pipelines, annotation, validation, and end-to-end machine learning outcomes. The role collaborates across machine learning, software, hardware, product, and data annotation teams to deliver production-ready solutions.
Responsibilities
- Build and maintain ETL pipelines that prepare structured and unstructured data for machine learning applications
- Clean datasets and perform feature engineering to support model development
- Annotate and review image data throughout the machine learning workflow (This is a core responsibility of the role, not a secondary task)
- Use Python, SQL, and statistical analysis to explore data and uncover actionable insights
- Train, fine-tune, evaluate, and experiment with deep learning models, primarily for computer vision applications
- Own machine learning outcomes end to end - from data quality and model performance to deployment and measurable product impact
- Collaborate with the annotation team to improve data quality, labeling practices, and machine learning workflows
- Partner with machine learning and software engineering teams to productionize, deploy, and monitor models
- Help make machine learning processes, capabilities, and results accessible to teams across the company
- Make sound technical decisions independently and drive projects forward with a high degree of autonomy
Skills
- * 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, with a focus on computer vision
- * Experience applying semantic segmentation to a real-world business or production use case
- * Strong Python programming skills and experience with libraries and tools such as PyTorch or TensorFlow, Jupyter, pandas, NumPy, and Matplotlib
- * Experience using AI-assisted development tools thoughtfully to improve productivity, quality, and speed
- * Experience performing statistical analysis and rigorously evaluating machine learning models
- * At least two years of experience working with a major cloud platform such as AWS, GCP, or Azure
- * Working knowledge of MLOps practices and the principles required to deploy, monitor, and maintain reliable machine learning systems in production
- * Strong analytical, programming, and problem-solving skills
- * Ability to work effectively in a fast-paced startup environment, iterate quickly, and balance speed with appropriate quality standards
- * Strong communication and collaboration skills, including the ability to work effectively with cross-functional teams
- This is a remote position aligned with U.S. Central working hours. Travel is a regular and essential part of the role, accounting for up to 10% of your time, including company team summits
- Candidates should be comfortable working in active production environments that may be greasy, loud, cold, and physically demanding. Most travel will be within the United States, although occasional international travel may be required. Some trips may be scheduled with only one or two days' notice, but we provide advance notice whenever possible. Comp days are provided when weekend travel is required
- * Experience developing and deploying computer vision models for real-world applications, including image classification and object detection
- * Experience deploying models at the edge, including balancing model size, accuracy, and performance; optimizing models for GPUs; and working with resource-constrained devices
- * Familiarity with image annotation platforms such as FiftyOne or Roboflow
- * Experience designing, building, or maintaining ETL pipelines
- * Experience fine-tuning deep learning models
- * Ability to lead early-stage research projects and make progress despite risk, ambiguity, and evolving requirements
- * A strong commitment to building high-quality products that solve meaningful real-world problems
- * Experience deploying and supporting edge models in live industrial environments
- * Image-matching or image-similarity experience
- * Previous experience working at an early-stage startup
- * Deep learning side projects that demonstrate curiosity, experimentation, or technical depth
Benefits
- Home Office Stipend
- Medical Insurance
- Dental Insurance
- Vision Insurance
- 401(k) Plan
- Health Savings Account (HSA)
- Comp days are provided when weekend travel is required.
- Impactful Work - Contribute to meaningful projects that directly affect sustainability and the global food industry. Your voice impacts decisions on day one.
- Collaborative Environment - Work closely with a dedicated team of professionals passionate about making a difference.
- Growth Opportunities - Expand your skill set by tackling diverse challenges across the full tech stack.
- Flexible Work Arrangements - Enjoy the flexibility of a remote position with opportunities for in-person collaboration. Flexible work hours allow you to plan work around your life, not the other way around.
Company Overview