Machine Learning Engineer

ABOUT FLOVISION SOLUTIONS

FloVision Solutions is a remote-first startup focused on improving the food supply chain, starting with protein processing. We design computer vision and machine learning-assisted production processes to reduce food waste, improve QA, and enhance staff skills, using proprietary hardware and software to solve customer problems.

FloVision Solutions is a U.S.-based Series A startup with a remotely distributed team across the USA, UK and Ireland.

POSITION OVERVIEW

As a Machine Learning Engineer at FloVision Solutions, you will be responsible for designing, building, and testing deep learning features for our applications. You will support our current team in bringing commercial ready software to market. We are looking for a self-driven, inquisitive individual who wants to help us achieve our mission of reducing 1% of CO2 emissions through a reduction in food waste. This role is a remote position (U.S. Central working hours), with travel 1-3 times per year for in-person working opportunities. 

We are looking for someone to design, build and optimize FloVision's computer vision applications. You will be a founding engineer working on state-of-the-art machine-learning infrastructure and models, with an emphasis on data integrity and validation of results. You will have the chance to touch all parts of the production and experiment with the ML stack. You will work closely with the data annotation team to ensure high-quality datasets are being created to get the intended results out of ML architectures. 

As one of FloVision’s early employees you will help shape our product roadmaps and engineering culture.

KEY RESPONSIBILITIES

• Creating ETL processes with our data to assist our machine learning
• Cleaning and feature engineering of machine learning dataset, structured and unstructured
• Bringing SQL expertise to the team
• Uncovering insights into our data through machine learning processes
• Training deep learning models (NLP, LLMs, CNN)
• Deep learning experimentation
• Working with our annotation team to improve machine learning processes
• Assist in making machine learning more transparent across other departments 
• Collaborating with ML team and software implementation teams to productize models

REQUIRED QUALIFICATIONS  

• A Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
• Three years experience in the ML/data science lifecycle with a focus on computer vision
• Two years of experience with a cloud provider (AWS, GCP, Azure)
• Experience with semantic segmentation in a real business use case
• Experience in statistical data analysis and machine learning techniques
• Familiar with in-depth analysis and evaluation of machine learning models
• Background with analytical tools such as Jupyter, Pandas, NumPy, Matplotlib
• Strong understanding of the end-to-end machine learning process 
• Ability to thrive in a collaborative environment and communicate clearly and confidently with partner teams

PREFERRED QUALIFICATIONS

• Experience with computer vision models in the real world (image classification, object detection, semantic segmentation, etc.)
• Familiarity with MLOps platforms (MLflow, Weights & Biases, etc.)
• Familiarity with labeling platforms (CVAT or Roboflow)
• Experience with ETL pipeline processes
• Experience with deploying edge models, balancing model size and performance, optimizing performance on GPUs
• Strong programming skills in Python with 5+ years of demonstrated ability in using Python for machine learning modeling 
• Hands-on experience with fine-tuning deep learning models
• Expertise in using machine learning toolkits such as PyTorch, TensorFlow, etc.
• Experience developing and optimizing algorithms that run efficiently on resource constrained platforms
• Ability to drive early-stage research projects with risks and ambiguity
• Passionate about delivering high-quality products, seeking to solve everyday problems in innovative ways
• Excellent programming, problem solving and analytical skills
• Excellent communication and collaboration skills in a multi-functional setting

Candidates with this experience will stand out

• Bonus: Production deployment experience for edge applications
• Bonus: Image-matching experience
• Bonus: Previous startup experience
• Bonus: Interesting deep learning side projects

INTERVIEW PROCESS OVERVIEW

Throughout the process, you'll have multiple opportunities to showcase your skills and experience, and we will aim to keep communication transparent and timely as we move through each step.

Stage 1: INITIAL APPLICATION & VIDEO INTRODUCTION
As part of your application, please submit a short 1–2 minute video introducing yourself and sharing why you’re excited about this role at FloVision Solutions. This helps us get to know you beyond your resume and understand what draws you to our mission. Your video doesn’t need to be polished - a simple phone recording is perfect. Applications without a video will not be considered.

Stage 2: BEHAVIORAL INTERVIEW (via Google Meet)

Stage 3: TECHNICAL INTERVIEW (via Google Meet)

Stage 4: FINAL INTERVIEW (via Google Meet)

JOB OFFER:
Upon successful completion of all stages, selected candidates will receive a formal offer to join FloVision Solutions.

BENEFITS

• Home Office Stipend
• Medical Insurance
• Dental Insurance
• Vision Insurance
• 401(k) Plan
• Health Savings Account (HSA)

WHY JOIN US?

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.

FLEXIBLE WORK ARRANGEMENTS: Enjoy the flexibility of a remote position with opportunities for in-person collaboration.

DIVERSITY AND INCLUSION

At FloVision Solutions, we believe innovation stems from diverse perspectives. We are committed to a workplace that supports and includes a variety of voices and identities. Candidates of all backgrounds and experiences are encouraged to apply.