Machine Learning Engineer/Data Scientist
We are looking for a skilled and motivated Data Scientist/ML Engineer to join our dynamic team at Quantori.
Responsibilities:
Own development data science tools and products (e.g., from last mile data engineering to in-dev or production ML models, Tableau dashboards, chatbot agents, etc.), ensuring their reliability, scalability, and business relevance
Design and implement data science solutions such as predictive models, NLP, and GenAI applications
Collaborate with cross-functional stakeholders to understand their needs and perspectives and drive technical development towards meeting those needs
Support/contribute to the planning of data science initiatives and contribute to the development of business cases (business case ownership will be elsewhere)
Solving problems/issues (Last mile data engineering (Snowflake, DBT))
What we expect:
Full Stack skills with a focus on modeling, with shading towards ML / MLOps
Experience in using Traditional ML (predictive models, NLP, some light black-box optimization (i.e. ORtools, CPLEX)
Experience with AI and GenAI (chatbot agents)
Solid Experience in Python and SQL
Expertise with platforms like Dataiku, Snowflake, Tableau, Gitlab, Streamlit, Artifactory, DBT, and working from a remote Linux development workstation
Experience in ML development and deployment (Dataiku, Gitlab) – predictive models, NLP, and chatbot agents
Expertise with cloud services such as AWS
Expertise in ML frameworks (e.g., TensorFlow, PyTorch/Lightning), programming languages (Python), MLOps technologies (e.g., Weights & Biases, AWS Sagemaker, Ray), and job scheduling frameworks (e.g., Slurm, AWS Step Functions)
EST availability is required
We offer:
Competitive compensation
Remote work
Flexible working hours
A team with excellent tech expertise
6-month contract with possible extension based on project needs and performance
Job Types: Contract, Temporary
Pay: From $50.00 per hour
Schedule:
8 hour shift
Application Question(s):
Are you available to work EST hours?
Work Location: Remote