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CVML Engineer, See and Spray

Roles & Responsibilities

  • Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
  • 1-2 years of relevant engineering work experience.
  • Understanding of the fundamentals of statistical learning.
  • Familiarity with the Python data science and ML stack: PyTorch, NumPy, pandas, scikit-learn.

Requirements:

  • Execute reproducible experiments on our large data catalog to further the understanding of model performance.
  • Implement and evaluate novel CVML techniques, ranging from CNNs to large Transformer-based Foundation models, to improve our products.
  • Execute and improve existing rigorous model evaluation pipelines.
  • Collaborate on debugging and troubleshooting issues in ML models.

Job description

We’re Blue River, a team of innovators driven to create intelligent machinery that solves monumental problems for our customers. We empower our customers – farmers, construction crews, and foresters - to implement safer and more sustainable solutions, driving increased profitability with less reliance on scarce labor. We believe that focusing on the small stuff – pixel-by-pixel and task-by-task - leads to big gains. 

Blue River Technology aligns with John Deere’s vision to “innovate on behalf of humanity” by quickly identifying and solving high-value, high-uncertainty challenges in AI, machine learning, computer vision, and robotics. BRT acts as a research and development flywheel, building not only new products but also new platforms that reliably create value for both Deere and its customers. From fully autonomous machines to highly precise farming equipment, BRT and Deere are partnering to create technical breakthroughs in industries like agriculture and construction. 

 

Summary

We are seeking a highly motivated individual to join our team as a junior/early-career CVML Engineer. This position supports the See & Spray CVML team within Blue River Technology and works in a multi-disciplinary team with the mission of bringing See and Spray to farms around the world. Our ideal candidate (you!) will play a crucial role in implementing Data-Centric AI practices for the See & Spray project. You have an analytical mind and take a data-driven approach to answering questions. Your contributions will be instrumental in driving the success of our machine learning initiatives and enabling evidence-based decision-making throughout the company.

  • Employment Type: Full-Time
  • Work Location: Remote in the United States
  • Visa sponsorship: Open to visa sponsorship. 

Job Responsibilities

A combination, not necessarily all-inclusive, of the following:

  • Execute reproducible experiments on our large data catalog to further the understanding of model performance.
  • Implement and evaluate novel CVML techniques, ranging from CNNs to large Transformer-based Foundation models, to improve our products. 
  • Execute and improve existing rigorous model evaluation pipelines.  
  • Collaborate on debugging and troubleshooting issues in ML models.
  • Lean into the responsible use of AI for software development.

Required Experience and Skills

  • Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
  • 1-2 years of relevant engineering work experience.
  • Understanding of the fundamentals of statistical learning.
  • Familiarity with the Python data science and ML stack: PyTorch, NumPy, pandas, scikit-learn.
  • Strong problem-solving and analytical skills with a keen attention to detail.
  • Ability to work collaboratively in a team environment and effectively communicate complex technical concepts.
  • Passion for emerging technologies, artificial intelligence, and computer vision.

Preferred Experience and Skills

  • Prior experience or coursework in CVML, natural sciences, and reproducible research.
  • Knowledge of data visualization best practices and effective storytelling with data.
  • Understanding of data modeling and database design principles.
  • Familiarity with agricultural technology, agronomy, or farming.

Only individual applicants will be considered. We do not work with unsolicited third-party agencies or proxy interview services. 

At Blue River, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $100,000 – $176,000/year for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. This position is also eligible for an annual performance bonus and a competitive benefit package. During the recruitment process, we may identify an alternative role or level to which you are more suited. If your ideal role at Blue River differs from the advertised position, we will provide an updated pay range as soon as possible during the hiring process.

We’re passionate about creating an inclusive workplace that promotes and values diversity. While we have more work to do to advance diversity and inclusion, we’re investing in our programs, including recruiting, mentorship, career development, and learning & development, to ensure they support our Diversity, Equity, and Inclusion goals. We support each employee in living a full life, enabling a thriving career, and accomplishing a meaningful, challenging mission while collaborating with incredible people. We are dedicated to building a diverse and inclusive workplace, so if you’re excited about this role but your experience doesn’t align completely with the job description, we encourage you to apply anyway.

We are an equal-opportunity employer and do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request an accommodation.

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