Senior Machine Learning Engineer
Fremont, CA /
About ProbiusDx Inc.:
We are Probius, an emerging venture-backed life science company developing next generation biochemical analysis solutions that combine quantum sensing and AI. Our technology yields a high-fidelity digital representation of the biochemistry of health for more detailed and predictive insights.
At Probius, we hire the most innovative talent to enable our partners and customers with solutions for their most challenging bioanalysis problems and we strive to extend the boundaries of what is possible. We foster the spirit of innovation by promoting responsible risk taking, open-mindedness, scientific excellence and integrity, open communication, and accountability as individuals and as a team. We are nimble, gritty, and unafraid to explore outside our comfort zone, and motivated to enable human wellness through deep technology and scientific discoveries, while maintaining a healthy work/life balance.
As Senior Machine Learning Engineer you will be front and center in defining and implementing the machine learning stack and infrastructure that underpins the Probius offering. This includes the optimization, implementation and deployment of our ML-based data analysis solution which is a key element of our biomolecular testing platform as a service. The ML solution encompasses data acquisition, storage, cloud-based computing, deployment and pipelining of data and machine learning models. Like all employees in the company, you will have a hands-on role with a high degree of autonomy, and this requires someone with a self-starter mindset. You will be responsible for the development, implementation, validation and maintenance of the ML infrastructure defined by internal R&D and customer requirements and collaborate directly with company management as well as the product application and marketing teams.
Your responsibilities include:
- Build and design machine learning pipelines, with existing and new databases
- Evaluating model performance and developing selection criteria for pushing to production
- Integrating ML output with customer-facing APIs and other interfaces
- Engaging with internal customers and business development teams to formulate product requirements
- Scoping project activities, estimating resourcing requirements and organizing resource allocation
- Creating and maintaining design documents for creation of MVPs through to product development; managing end-to-end implementation of ML product stack and databases.
- Communication and knowledge sharing with technical and non-technical team members to facilitate seamless product development
- Inducting best-in-class practices with regards to database engineering and ML-centric product development
- Interfacing with DevOps, as needed, to manage and roll out releases
Your expertise and qualifications:
- Minimum qualifications:
- 4+ years of hands-on experience in designing and building ML pipelines and databases, in cloud-native environments (AWS, Azure)
- Prior experience in working with MATLAB, R
- Expertise in ML pipeline tools like Python, Kubeflow, MLFlow, MLLib and others.
- Expertise in data pipeline tools like Spark, Cassandra, Kafka, or Airflow
- Knowledge and know-how for infrastructure specification in AWS/Azure
- Prior experience with deploying NoSQL and SQL technologies like PostgresSQL, MySQL, Cassandra or MongoDB
- Experience with working in agile software development environments
- Experience in building machine learning and data analysis engines, and transitioning to production
- The following qualifications are considered a plus:
- Experience in developing ML-products that are Life-Sciences focused
Working with us:
ProbiusDx is an equal opportunity employer that values and respects the importance of a diverse and inclusive work force. Our company offers a competitive salary and benefits package, a professional work environment and opportunities for growth. Not only you will be joining a highly skilled and tight-knit team where every engineer, product manager and scientist make a significant impact on customer solutions, we also have a good work/life balance making our environment welcoming, fun, and adaptive.