ML Engineer, Deep Learning & NLP

San Francisco
Engineering
Full Time
At Forethought, we're solving the world's hardest problems in Natural Language Understanding to build an "answer engine" for the enterprise. Customers use our answer engine to give employees and customers access to the right information at the right time. Our mission is to "enable everyone to become a genius at their job".

Founded in 2017, Forethought is funded by some of the top VC's and Angel Investors in Silicon Valley. (Hint: We're backed by some of the same investors as Twilio, Lyft, and Front)

We're looking for world-class Deep Learning and Natural Language Processing ML Engineers to come join our team! We're looking for folks with a growth mindset, who love to solve the world's hardest problems, and want to have an impact on the world.

You will be responsible for researching and implementing state-of-the-art algorithms in Question Answering, Machine Reading Comprehension, Recognizing Textual Entailment, Document Classification, Text Analytics, Sentiment Analysis, and Automated Knowledge Graph Extraction.

What a typical week may look like at Forethought:
Improve our core Question Answering algorithm
Reading and researching state-of-the-art papers in NLU problems
Inventing new NLU algorithms
Working with a unique dataset of 1M+ customer documents, support tickets, and natural / unstructured data sources
Build Deep Learning models in TensorFlow for GPUs and CPUs
Work with Backend Engineers to ship your models to production
Work to publish new research in top papers (e.g.: NIPS) and Arxiv

What we value and look for in a Deep Learning & NLP ML Engineer:
MSc or PhD in Computer Science, Mathematics, or a related technical field
2+ years industry experience in Data Science or Machine Learning teams
Proficiency in Python, R, or Java
Experience in modern Deep Learning and Natural Language Processing / Natural Language Understanding (NLP, NLU), including Neural Networks, RNNs, seq2seq+attention models, and real world machine learning in TensorFlow (incl. regularization, cross-validation, dropout)
Experience building production-ready NLP systems
Familiarity with non-standard machine intelligence models (Reinforcement Learning, Hierarchical Temporal Memory, Capsule Networks) is a plus
Familiarity with Distributed systems (Docker, Kubernetes, Kafka, Spark, Redis, AWS S3/EC2/RDS/KMS, MongoDB, or Lucene) is a plus
Adaptable, humble, and interested in pushing the boundaries of what's possible

What you get:
A fast-paced and collaborative environment
Work with world class talent (our team has experience from Facebook, Palantir, and LinkedIn Data Science; we have 2 ACM ICPC World Finalists; and Researchers from Harvard, Waterloo, EPFL, and University of Alberta)
A chance to be a defining/founding member of the team, with equity to match
A chance to work on the edge of research
A mix between research and industry, at a startup!
Medical, dental and vision coverage 
Unlimited PTO policy