1. Basis Set Ventures - AI Engineer

Basis Set Ventures is a Venture Capital firm that invests in enterprise artificial intelligence companies. We are looking for highly motivated and talented individuals who are excited about artificial intelligence, working with some of the world’s best entrepreneurs, operators and VCs to build a new enterprise. We want energetic and motivated people who thrive in an unstructured, diverse and welcoming environment.
We are seeking data scientists and engineers including those who are interested in transitioning into an investor role in the future, you will work with the partners to

  1. Explore creative ways to source and evaluate deals
  2. Build tools that source and evaluate deals at scale
  3. Conduct technical due diligence
  4. Help advise and support portfolio companies on engineering and data science projects
  • Graduate of a top tier university; PhDs in EE, CS, Machine Learning, Physics, or a quantitative discipline preferred
  • Experience with technology, including but not limited to tech startups
  • Passion for technology and startups is a must
  • Excellent academic record, creativity, analytical abilities, and ethics
  • Entrepreneurial experience and professional network in the Bay Area, East Coast (e.g. Boston) or an area in the United States with a strong tech ecosystem preferred
  • Ability to establish and maintain good relationships with colleagues and entrepreneurs
    Contact: bsv@basisset.ventures

2. Clara labs – Machine Learning Scientist

Clara Labs is establishing a new class of virtual assistant that understands you like a person, but operates at the scale, speed, and persistence of a machine. To do this, we mix intelligent automation software with remote human contractors to form an efficient, distributed remote-knowledge-work service.

You will work on soup-to-nuts development of novel algorithms informed by our unique applications and constraints. Individuals in this role design data collection strategies, frame the right problems to solve, develop models, measure and compare model performance, and integrate these models into production features.
ML team members embed with a product-focused engineering team to ensure that:

  • ML predictions are relevant and usable within the primary platform;
  • confidence metrics can be integrated into automation systems; and
  • data/annotation collection facilities for each problem are baked into our platform.
    You have experience in one of the following and familiarity with several others:
  • LP / computational linguistics: techniques (e.g., pos tagging, dependency parsing, chunking, classification, …) and tools (e.g., Stanford NLP, nltk, …).
  • Bayesian inference: e.g., topic modeling, graphical generative models.
  • ML methods: e.g., svms, random forests, convex optimization, transfer learning.
  • Deep learning: rnn / cnn architectures, algorithms (e.g., rmsprop, adadelta, adam, …), and tools (e.g., theano, torch, tensorflow, …).
  • ML in practice: e.g., selection bias mitigation, ROC analysis, field performance analysis, data mining.
  • ML systems: event-driven real-time ML systems, pipelining and processing frameworks (e.g., Spark, Lucene, EMR).
    Nice to have(s):
  • M.S. or Ph.D. in CS, EE, or equivalent.
  • Industry experience with ML systems is strongly preferred.
    Communicating machine learning results and capabilities are important on this team. Please include a cover letter explaining why you think you are a great match for Clara.

3. Roxy - Machine Learning, NLP Engineer


4. Scale - Machine Learning Engineer


5. Scale - Backend Developer


6. Sourceress - Machine Learning Engineer

Sourceress is an AI sourcer who scales your recruiting team. We make it dramatically faster and easier for great companies to hire great people. Our mission is not just to fix hiring, but to fundamentally change the way that human mental effort is allocated.

We’re looking for ML engineers who are passionate about making a positive impact. We have a long list of interesting machine learning problems that are core to our product—for example, building models to predict personality attributes and professional skills from a resume so that we can understand someone well enough to automatically decide (with very high precision and recall) if they are a good fit for a particular role.

Our stack: Python (Django, nltk), AWS (S3, PostgreSQL), Javascript (React)

If you…

  • Love programming
  • Ship tons of code quickly
  • Want to build ML models that drive the business
  • Are empathetic, highly systematic, intensely driven, and intellectually curious
  • Care about improvement at both the individual and global scale

Then we should have a conversation, because we’d enjoy working together. Help us create a world where all 7 billion people work at jobs that they loved, do things that they’re great at, and work for companies that are solving meaningful problems.