Machine Learning Engineer

We’re looking for a bright Machine Learning Engineer to join our team of machine learning experts. Our team is growing, and so is our appetite for cutting edge work. You will have many chances to bring work from theory to practice, enrich Tulip’s intellectual property, and share it before key people in the company and outside.

We are looking at hard, data-rich problems, with immense scale and unique opportunity for impact on large organizations. Your first goal will be to research the data analysis needs of our clients, and implement those on our platform. Next you will deploy your work and monitor its performance with live installations worldwide.

About us

At Tulip, we’re using technology to empower the people who build our world. We’re at the technological forefront of disrupting the manufacturing industry. We build tools to augment the people from the factory floor up to the highest ranks in the organization. We sense the people in the workstations, the processes, the work pieces, the machines, the tools and even the environment. All this creates incredible amounts of data, ripe for insight extraction. Join us if you want to help create the next industrial revolution.

The job

  • Develop data analysis pipelines from ingest to postprocessing
  • Train machine learning models that solve hard, large-scale problems
  • Continuously improve the model deployment pipeline
  • Track and monitor the performance of your model outcomes
  • Contribute to the IP of the company
  • Collaborate in driving sales with your technological expertise
  • Bring up new data-driven features from ideation to production

You

  • Curious about data-driven software and machine learning solutions
  • Have experience in turning data into insights, and insights into actions
  • Understand the latest work in deep learning, and want to stay in touch
  • Demonstrate your own work in front of peers
  • Are committed to stepping up and making your path as a data-driven innovator

Key requirements

  • A degree or several in computational sciences (CS, Math, Applied Physics, Engineering, Statistics, Computational Cognition, etc.) or equivalent industrial experience in an engineering role.
  • Demonstrated capacity for realizing non-trivial machine learning projects, e.g. on GitHub, Kaggle
  • Demonstrable mathematical reasoning about data and numerical problems in multiple aspects: linear algebra, calculus, probability, algorithmics and optimization.
  • Advanced experience in relevant major languages: Python, C++
  • Experience with deep & machine learning libraries: Tensorflow / Keras / PyTorch / MXNet / Gluon, Scikit-learn, Pandas.

Bonus skills

  • Experience with MR, data pipelines and ETL in the various clouds (AWS, GCP, Azure), e.g. DataProc, EMR, Spark, Hadoop.
  • Experience with cloud-based deployment of ML models, e.g. SageMaker, GCP AI Platform, Azure ML service
  • Experience with edge-based ML inference
  • Experience with ML parallelism, MPI, e.g. Horovod, Tensorflow parallelized training
  • Working in containerized environments, e.g. Docker, Kubernetes
  • Experience with relevant visualization libraries, e.g. matplotlib, Seaborn, Bokeh, Plotly
  • Experience in computer vision or language processing algorithm development.

Working at Tulip

We are building a strong, diverse team that values hard work, families, and personal wellbeing. Benefits of working with us include:

  • Direct impact on product and culture 
  • Company equity
  • Competitive benefits package including Health, Dental, Vision, HRA, Commuter, and 401k
  • Flexible work schedule and unlimited vacation policy
  • Fully stocked office kitchen with weekly meals and beer on tap 
  • Company outings and happy hours 
  • Fitness subsidies
  • Dog-friendly office

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Even if you don't check every box, but see yourself contributing, please apply. Help us build an inclusive community that will transform manufacturing.


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