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Biofonic

Data + ML Engineer & Researcher (Acoustic Signal Processing)

London
£60k – £70k/yr
Posted about 22 hours ago
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ML + Data Engineer & Researcher (Acoustic Signal Processing)

Passionate about making a difference and building groundbreaking new technology?

Biofonic is looking for a Machine Learning Engineer/ Researcher to help us on our mission to accelerate sustainable agriculture and conservation research.

This is an excellent opportunity to make a big impact and gain hands-on experience at a dynamic, early-stage startup building a novel solution for soil ecosystem intelligence.

About The Role

Location: London, UK

Salary Range: £60-70k + EMI share options

In this role, you will play a critical part in designing and developing our next-generation acoustic sensor hardware and novel machine learning models. You’ll get your hands dirty (literally!) and work closely with the entire cross-functional team, including the founder, lead hardware engineer, and our academic advisors and commercial partners across entomology, soil science, eco-acoustics, and agriculture to create innovative solutions.

We are seeking a talented and driven Data + ML Engineer with signal processing expertise to process and analyze data from our unique acoustic sensors, validating sensor performance and assessing data quality to inform prototype design and engineering decisions. Your work will be critical in transforming unique raw sensor data into actionable insights to achieve our machine learning goals.

Your work will influence the future of sustainable agriculture by providing farmers and conservation managers with accessible, high-impact tools needed to save our depleting arable soils and accelerate new discoveries about the planet’s least understood and most biodiverse ecosystem - Soil.

We are prioritizing folks with founding team member potential. Your ability to exhibit thought leadership and strong product strategy skill set within an evolving technological landscape will be key, as we work to shape the future of farming.

Key Responsibilities

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  • Data Processing: Implement data preprocessing pipelines to clean, normalize, and transform raw sensor data for model training and evaluation.
  • Model Development: Design, develop, and refine machine learning models to analyze acoustic sensor data.
  • Algorithm Optimization: Optimize algorithms for performance, accuracy, and scalability.
  • Collaboration: Work closely with our team and across our research and pilot partners to ensure seamless integration of ML models with sensor hardware and field applications.
  • Research: Stay current with the latest advancements in machine learning, AI, agtech, and acoustic analysis to continually enhance our products.
  • Deployment: Develop and maintain production-level code for deploying ML models to devices and cloud platforms.
  • Data Systems: Design, build, and maintain data architecture.
  • Basic Software Development: Build a beta application for commercial trial users.
  • Documentation: Create comprehensive documentation for data architecture, model design, training procedures, and deployment processes to support ongoing development and compliance.

Qualifications

Education: Master’s or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field.

Experience: 3+ years of experience in signal processing and machine learning engineering, with a track record of deploying models in production environments. Strong preference for candidates with applied experience in real-world signal analysis, ideally with acoustic signal data or analogous signal types like ultrasound or frequency-dependent signals.

Technical Skills:

  • Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Deep experience with signal processing techniques and data processing tools.
  • Experience with data pipeline management and software engineering skills.
  • Analytical Skills: Strong problem-solving abilities and the capacity to analyze and interpret complex datasets.
  • Team Player: Excellent communication and teamwork skills, with the ability to collaborate effectively in a multidisciplinary environment.
  • Passion: A genuine interest in sustainable agriculture and environmental stewardship.

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About Biofonic

We’re passionate believers in regenerative and life-centered design, and our holistic, values-driven, interdisciplinary approach to delivering impact permeates everything we do.

What We Offer

  • Impact: Be part of a mission-driven company dedicated to making a real difference in farmers’ and land managers’ ability to transition to net-zero, nature-friendly methods.
  • Innovation: Work on cutting-edge technology and research spanning acoustics, ML, AI, user behavior, sustainability, agriculture, and ecology.
  • Growth: Ample opportunities for professional development and career advancement within role and in partnership with our sponsoring accelerator programs and advisory network. Opportunities to pursue value-added work outside your role scope through 20% projects.
  • Culture: A collaborative, inclusive and fun work environment that values creativity and innovation.
  • Benefits: Competitive salary, employee options, flexible working arrangements, and opportunities to visit our partner sites across the UK and see your work in action.

We value diversity of talent, ideas and perspectives and are an equal opportunity employer. If you are unsure if it’s a perfect fit but are excited about what we are working on, we encourage you to apply!

How To Apply

Please submit your resume and a cover letter detailing your experience and why you are passionate about this role to alex@biofonic.earth with the subject line "Biofonic ML Engineer."

Join us at Biofonic and help shape the future of sustainable farming and interspecies AI!

Photo by Greg Willson on Unsplash

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Skills

Acoustic Signal Processing
Machine Learning
Python
TensorFlow
PyTorch
Scikit-learn
Data Pipeline Management
Software Engineering
Algorithm Optimization
Data Architecture
Signal Analysis
Production Deployment

Location

London, England, United Kingdom

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