Senior Machine Learning Engineer

Remote • 3.0% - 5.0%

ReFocus AI


Role Location

  • Remote

Compensation

3.0% - 5.0%

Employees

< 10 people

Address

4581 Bancroft St
San Diego, CA, 92116, US

Tech Stack

  • Angular
  • Django
  • AWS
  • PostgreSQL

Role Description

Overview

ReFocus AI is looking for a Senior Machine Learning Engineer to join our fast-paced team and help drive ReFocus adoption in North America. In this position, you will have the opportunity to be part of a sales enablement AI-platform that derives insights from every interaction and helps match customers’ wants and needs with suppliers’ products and services at scale. You will work closely with your colleagues to build and deploy advanced machine learning models for sales teams of all sizes, from multinational insurance entities to Fortune 500 logistics companies.

The ideal candidate will possess a strong computer science background. The candidate should have demonstrated experience building and refining machine learning models in past roles, and understand different model types, ideal use cases, and limitations. The ideal candidate will also have a demonstrated ability to think strategically about business, product, and technical challenges, with the skill-set to serve as a subject-matter expert (SME) within the product team.

*Please note that this is currently a part-time, equity only position with the potential to become a full-time paid position. *

Responsibilities * Develop new and continually refine existing machine learning models. * Support the full ML lifecycle including ML Ops and specialized infrastructure like AWS Sagemaker. * Design, implement, and continuously expand data pipelines by performing extraction, transformation, and loading activities. * Serve as a machine learning SME for the product team. * Work collaboratively with business development and support to answer questions and troubleshoot problems. * Keep abreast of new trends and best practices in the technology landscape.

Required Qualifications * 3+ years of experience as a Machine Learning Engineer. * 3+ years transforming data in various formats, including JSON, XML, CSV, and zipped files. * 2+ years developing flexible ontologies to fit data from multiple sources and implementing the ontology in the form of database mappings / schemas. * 2+ years maximizing model performance through feature engineering and optimization. * Proficiency deploying scalable models to AWS using Sagemaker. * Demonstrable experience coding in Python using scientific libraries like NumPy, SciPy. * Understanding of data structures, software design principles and algorithms. * SQL knowledge (query performance tuning, index maintenance, etc.) as well as an understanding of database structure * Knowledge of data modeling principles * Deep knowledge of traditional ML concepts such as GMMs, SVMs, trees, and boosting as well as more recent deep learning fundamentals.

Education & Experience Possess a BS or MS candidate in Computer Science, or Machine Learning.

Preferred Qualifications * 2+ years leading the design, implementation, and deployment of new machine learning algorithms and methodologies. * Familiar with Angular, Django, and PostGreSQL. * Experience presenting research at technical conferences. * Providing technical guidance to product teams on the choice of machine learning approaches appropriate for a task. * Experience in deployment of machine learning solutions to a web application environment. * Experience integrating products into enterprise systems * Experience developing flexible data ingest and enrichment pipelines, to easily accommodate new and existing data sources. * Experience with software configuration management tools such as Git/Gitlab, Salt, Confluence, etc. * Experience with continuous integration and deployment (CI/CD) pipelines and their enabling tools such as Jenkins, Nexus, etc.

About ReFocus AI

ReFocus AI derives insights from every customer interaction to identify what and when a prospective customer will purchase a product or service.

Company Culture

We are guided by our five core values: - Love what we do - Honesty and Commitment - Be humble - Make mistakes, fail fast, and learn hard - Ask questions and give feedback

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