Shake (11-50 Employees, N/A 2 Yr Employee Growth Rate)
We’re an established high-growth business with thousands of paying customers and a team of 20+. We are searching for a Machine Learning Engineer (Work from Anywhere) that can help us build and improve data clustering algorithms to build an index that will be used by some of the biggest companies in the world. You’re a proactive, excited about ML, and self-motivated individual eager to learn and take ownership of your work. You love communicating and working with other ML and Python engineers to build ML models and algorithms for various products at Shake.
Being bootstrapped (not venture-backed) and fully remote, we don’t strive for growth at all costs and are building a company we can be proud of and enjoy working for.
What you’d be expecting:
- Research and develop innovative ML strategies for challenging problems that will affect future Shake products.
- Collaborate with our ML engineers to improve ML algorithms and solutions.
- Self-motivated, an excellent problem solver, and a go-getter.
- Have strong programming skills with tried experience crafting, prototyping, and delivering advanced algorithmic solutions.
- Able to create flexible, fast, and memory-efficient algorithms for computationally expensive problems (NP-Hard).
- Able to work well with change and ambiguity.
- Familiar with attention mechanisms, transformers, and N-Grams + Tf-Idf.
- Familiar with Word Embedding techniques like Word2Vec, GloVe, or BERT
- Familiar with the above techniques in at least one library like PyTorch, TensorFlow, or GENSIM.
- Has experience with Incremental Record Linking to find clusters in vast datasets.
- Familiar with Python programming language, Git/GitHub.
Nice to have:
- Has implemented an ML algorithm for analyzing the mood of Twitter tweets.
- Familiar with Databases and SQL.
- Have experience working with ElasticSearch.
Salary range: $24,000 – $48,000 /year (USD, gross)
Work from anywhere
️ 26 days of paid time off
Co-work expenses covered (up to $300/m)
$500/year learning budget
️ Yearly retreat in incredible locations (the last one was in Thailand!)