Job description

Salary Range: $130000 to $160000 Annually Onsite in Oshkosh, WI or New Hudson, MI Core requirements • 5+ years of experience; 6 years may be appropriate , according to the manager. • AI-savvy and business-savvy, with strong business relationships and experience working directly with business stakeholders—not solely back-end development. • Ability to manage work end to end and personally deploy and deliver the solution. Technical Expertise • Expert proficiency in Python (including NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow) and advanced SQL. • Strong hands-on experience building supervised/unsupervised learning pipelines, deep learning models, natural language processing (NLP), and modern Large Language Model (LLM) architectures. • Proven track record utilizing enterprise cloud ecosystems (AWS, Azure, or GCP) and distributed compute systems (Databricks, Snowflake, Apache Spark). • Demonstrated familiarity with model tracking, containerization, and orchestration platforms (e.g., MLflow, Docker, Kubernetes, Kubeflow, Airflow). • Proficiency in presenting findings via business intelligence and visualization tools (e.g., Power BI, Streamlit).

Requirements

Must-haves

$130000 to $160000 Annually
Onsite in Oshkosh, WI or New Hudson, MI
5+ years of experience; 6 years may be appropriate , according to the manager.
AI-savvy and business-savvy, with strong business relationships and experience working directly with business stakeholders—not solely back-end development.
Ability to manage work end to end and personally deploy and deliver the solution.
Technical Expertise
Expert proficiency in Python (including NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow) and advanced SQL.
Strong hands-on experience building supervised/unsupervised learning pipelines, deep learning models, natural language processing (NLP), and modern Large Language Model (LLM) architectures.
Proven track record utilizing enterprise cloud ecosystems (AWS, Azure, or GCP) and distributed compute systems (Databricks, Snowflake, Apache Spark).
Demonstrated familiarity with model tracking, containerization, and orchestration platforms (e.g., MLflow, Docker, Kubernetes, Kubeflow, Airflow).
Proficiency in presenting findings via business intelligence and visualization tools (e.g., Power BI, Streamlit).

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonsqlllmawsazuregcpdockerkubernetes

Platform: jobdiva
Effort: medium