You are an experienced ML Engineer who is excited to join a small team of seasoned entrepreneurs and technologists tackling what we see as one of society’s most pressing problem: making time matter in a world that hijacks our attention.

As the foundational hire for our machine learning practice, you must have experience building machine learning models with different frameworks and technologies. Experience working on enterprise SaaS products using a modern development stack is a great asset to have, and so is experience using the latest AI stacks.

You are a lean experimentor, focused on shipping and iterating. You to deliver results in 1/3 the time that most competent people think possible. You exercise extreme ownership, cast no blame, make no excuses. You are obsessed with data, and stay connected to the details. You see it as your obligation to challenge decisions when you disagree, and seek the scrutiny of your own ideas. Finally, you exemplify grit, grace, and gratitude – grit to fuel pursuits with the fire of determination; grace to embrace living through empathy and compassion for others; gratitude to remind yourself of the abundance you have.

* Are responsible for developing our core data science engine, which turns incoming data from a company’s workplace stack into an understanding of time and attention.

* Conceptualize and apply various data techniques science to large data sets, ranging from training neural nets, to fine tuning foundation models.

* Build the foundations of ML at Parable – an opportunity to apply what you think are the best systems and methodologies to solve our customers’ problems.

* Work closely with our founding Staff Engineer, founding Data Engineer, and founding AI Engnineer to deliver unique insights to customers.

* Have the opportunity to become the Head of ML at Parable, a company where ML will play a foundational role.

* Report to our CTO - Clint Robinson. Clint has 20 years of experience building technology products. He was founder, CEO and CTO of an enterprise SaaS company which was acquired for $200 million after 3 years.

* Strong expertise in Python, R, possibly Java.

* Proven experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, pandas).

* Demonstrable experience with both supervised and unsupervised learning models, including deep learning, regression, and clustering techniques.

* Proficient in developing and deploying models in both cloud-based environments (AWS, Azure, GCP) and on-premises.

* Strong ability to interpret and communicate data insights to non-technical stakeholders.

* Experience with big data technologies (e.g., Hadoop, Spark) is desirable.

* A Master’s degree or Ph.D. in Computer Science, Data Science, Statistics, or a related field is preferred.

* Get deep in the data from our design partners, proposing and trialing methodologies to transform unstructured data into an understanding of time.

* Deploy neural nets out of Python, and train models to generate the right outcomes.

* Write code in Python and R.

* Experiment rapidly to deliver learnings and results in the first month.