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Machine Learning Engineer at InCloudCounsel (San Francisco, CA)

InCloudCounsel is hiring a Machine Learning Engineer to join our fast-growing company, headquartered in San Francisco. We have fundamentally changed how corporate legal work is done and it is quickly catching on as we scale. Machine learning is a significant part of our strategy as our platform and services grow.

You will work in a lean engineering team whose mission is to build ML-enabled tools for our users - we are bringing technological innovation to an industry traditionally weighed down by inefficiencies and skyrocketing costs. Your role will be to help people do their work faster and with increased accuracy while simultaneously driving down the cost of legal work. You will do this by building a platform for machine learning and collaborating with the product team to deliver functionality that creates value and freedom for our clients and attorneys. This position reports to our Director of Machine Learning. 

This is a new team working with paradigm-shifting technology at its cutting edge. It is an opportunity to take the exciting new research of natural language processing, neural networks, and machine learning systems to deliver real value to an industry that has historically been behind in technology. We have an incredibly rare and valuable opportunity in front us with the drive and resources to transform the legal industry. We believe strongly in open-sourced software and open research. 

There is a lot to do, and we are looking for resourceful engineers with the experience to pick up large projects and execute on them. As a founding member of the team, you will be shaping the future of machine learning at InCloudCounsel as well as the broader legal services industry.


  • Platform Tools: We have frameworks for training, storing, serving, and analyzing models that need to be built out in a thoughtful and elegant manner. These tools support the research we do. Additionally, we want to open source our work so it is important that it is of high quality.
  • Infrastructure: We run on Heroku and AWS, and there is a fair amount of data that exists and is processed through our systems. Additionally, there is a build, deployment, testing, and monitoring side that you will build and maintain. We run production systems that need to maintain uptime as data comes in around the clock.
  • Performance Engineering & Scaling: Machine learning is very data and compute intensive. Things need to scale along many dimensions, including model training (with accelerators or distributed systems), model storage, and model serving systems. We are already dealing with scaling issues and this will be a large part of your work.

Skills & Requirements

  • Experience: 4+ years of engineering experience. We need people who can take on projects end-to-end independently, from conception and prioritization to execution and delivery.
  • Programming Knowledge: Excellent knowledge of Python for data analysis, data processing, and server programming. We use Numpy, Pandas, scikit-learn, Tensorflow, spacy, and many other libraries. This is our preferred tech stack, but if you have comparable experience in a different stack that's fine too.
  • Problem Solving & Algorithms: You don't need to know how to code a red-black tree in ten minutes, but you do need the knowledge of how, when, and why. Our code needs to be efficient and scalable.
  • Science: Prior or tangential experience with machine learning or natural language processing is a plus, but only an interest is needed.
  • Data: Good knowledge of databases and data storage systems, schema design, performance, and limitations. We use S3, Postgres, and Redis, but experience with similar tech is fine too.
  • Systems Architecture: Excellent knowledge of systems design, microservices, caching, queueing, and real-time systems.
  • Infrastructure: Good understanding of systems operations tooling and infrastructure (Linux-based OSes, scripting, build and deployment tools, containers, any systems monitoring technology). We use Heroku, AWS, and Docker. We embrace managed services as well—whatever gets the job done.
  • Open source: Experience or interest in open source software is a plus! Bringing openness to a historically closed industry is an important goal for us.
  • Communication & Interpersonal Skills: We highly value communication at our company. Empathy, transparency, and respect are core values of ours, and we maintain a great culture this way.