ML Ops Engineer

Seattle, Washington San Francisco, California Chicago, Illinois St. Louis, Missouri


At Climate, our mission is to use technologies to enhance the sustainability and security of our global food value chain. Using field-verified data science models, Climate is shaping the future of sustainable agriculture across 180 million acres worldwide and counting. As the digital farming arm of Bayer Crop Science, we have the benefits and resources of an established organization while offering employees the opportunity to deliver significant individual impact alongside some of the brightest minds in life sciences. 

Grounded in our vision, ‘Health for all, Hunger for none’, our diverse team spends their days solving the world's most pressing challenges through sheer curiosity and dedication. In our learning-oriented and flexible environment, you can find us collaborating in a hybrid model that mixes on-site and remote work. 

Our LIFE values—leadership, integrity, flexibility, and efficiency—and our unique focus on health and nutrition demand that we create value for all stakeholders—today, tomorrow, and for generations to come. If you’re hungry to build a meaningful career helping empower farmers with sustainable digital farming systems, keep reading! 

The Opportunity 

Climate is revolutionizing the agriculture industry with a platform and products that are helping the world’s farmers sustainably increase productivity with digital tools. We are leveraging Machine Learning and Big Data to build meaningful products that allow farmers to produce enough food to help feed a growing population.    

We are looking for an ML Ops Engineer to join our production deployment team. We work with research scientists who are developing and prototyping ideas to get their models into our Field View platform. The team is highly collaborative and partners with data scientists, engineers, and product managers. We’re looking for someone with experience developing and maintaining Machine Learning Ops pipelines who can help us do the same while building tools to automate the path to productions. The ideal candidate is someone who has an interest in machine learning and would like to transition to the scaling, evaluation, and development of machine learning models, in the long-term. 

What You’ll Do  

  • Collaborate with data engineers, data scientists, and product teams to guide the translation of R&D prototypes into stable, testable, and maintainable production services  
  • Develop and deploy tools and services for our team to accelerate the production lifecycle and assessment of production readiness   
  • Help lead team members in executing continuous integration and continuous delivery (CI/CD) activities to release code into a Production environment  
  • Act as a consultant within the Science Organization on software engineering principles, code quality, and performance optimization techniques  
  • Apply software engineering rigor and best practices to machine learning, including CI/CD and automation  
  • Build model performance monitoring capabilities and data monitoring tools 

About You

What You’ll Need 

  • MS Computer Science, Engineering, Technology, Mathematics, Statistics, or related field with 3+ years of industry experience or BS + 5 years' experience  
  • Hands on coding experience with Python building end-to-end systems as an MLOps Engineer, Machine Learning Engineer, Software Engineer, or equivalent  
  • Experience in ML model development, orchestration, deployment, monitoring, support and creating and maintaining deployment pipelines with CI/CD tools  
  • Experience with cloud computing platforms like AWS, GCP, or other cloud providers developing with containers (e.g., Docker, Kubernetes) in cloud computing environments 

Nice To Haves  

  • Exposure to deep learning approaches and modeling frameworks (Py Torch, TensorFlow, Keras, etc.)  
  • Familiarity with MLflow or similar platforms like Kubeflow or SageMaker  
  • Experience building and evaluating machine learning models  
  • Strong understanding of software testing, benchmarking, and continuous integration  
  • Experience mentoring and teaching software development best practices to data scientists  
  • Ability to translate complex technical concepts to collaborations, decision makers, and non-technical audiences 

What We Offer

  • Base salary estimated range between $119,573-$197,407 annually, depending on the hiring location. You may also be offered bonuses, RSUs cash equivalent, or commission. 
  • Comprehensive health benefits including medical, dental, vision, life, and disability, as well as a Life Solutions Plan covering mental health benefits 
  • Industry leading 401K match of up to 10% 
  • Discounted access to Employee Share Purchase Plan program 
  • Professional growth opportunities including up to $10,000 college tuition reimbursement, access to upskilling platform, leadership training, mentoring and coaching programs, and short-term assignments (domestic and international) 
  • Yearly $500 WFH stipend for hybrid office employees 

Belonging and

At Climate, we strive to create inclusive experiences for candidates and employees alike in which a diverse set of perspectives and voices are represented. If this role sounds exciting to you but your experience doesn’t perfectly align with the job description, we still encourage you to apply. 

We’re proud to be an equal opportunity employer. This means we actively pursue ways to celebrate our differences and don’t discriminate based on race, religion, color, national origin, ethnicity, gender, sex (including pregnancy), protected veteran status, age, disability, sexual orientation, gender identity, gender expression, or any unlawful criterion existing under applicable federal, state, or local laws.  

If you need assistance or an accommodation due to a disability, contact us at [email protected] 

Learn more about our team and mission: