Senior Machine Learning Engineer

Next Ventures; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

A fast-growing data-driven organization in the United States seeks a Machine Learning Engineer to lead the design and optimization of predictive models. The ideal candidate will have a Master's or PhD, extensive experience in deploying ML models, and proficiency in Python alongside cloud platforms like AWS or GCP. Strong communication skills are essential for collaboration with both technical and non-technical teams. This role offers a chance to influence product strategy directly through innovative ML solutions.

Qualifications

• Strong experience building and deploying ML models in a production environment.
• Deep understanding of machine learning techniques (e.g. regression, classification, clustering, deep learning).
• Experience working with SQL, cloud platforms (AWS, GCP, or Azure), and modern data warehouses.

Responsibilities

• Lead the design, development, and optimization of predictive ML models.
• Analyze large, complex datasets to uncover trends and actionable insights.
• Deploy models into production environments and integrate via APIs.

Skills

Machine Learning techniques

Python

SQL

Communication skills

Problem-solving mindset

Education

Master’s or PhD in a relevant field

Tools

TensorFlow

PyTorch

scikit-learn

AWS

GCP

Azure

Git

Job description

We’re partnering with a fast-growing, data-driven organization that’s looking to bring on a Machine Learning Engineer to join a highly collaborative and innovative team. This is a key role where you’ll drive the development of predictive models that directly influence product performance and client outcomes.

What you’ll be doing:

• Lead the design, development, and optimization of predictive machine learning models
• Analyze large, complex datasets to uncover trends and actionable insights
• Partner with data engineering teams to build and maintain feature pipelines
• Evaluate and iterate on model performance using robust testing methodologies
• Deploy models into production environments and integrate via APIs
• Collaborate cross-functionally with product, engineering, and technical stakeholders
• Stay at the forefront of ML and data science advancements, bringing new ideas into practice

What we’re looking for:

• Advanced degree (Master’s or PhD) in a relevant field
• Strong experience building and deploying ML models in a production environment
• Deep understanding of machine learning techniques (e.g. regression, classification, clustering, deep learning)
• Proficiency in Python and common ML libraries (TensorFlow, PyTorch, scikit-learn)
• Experience working with SQL, cloud platforms (AWS, GCP, or Azure), and modern data warehouses
• Strong communication skills with the ability to work across technical and non-technical teams
• A proactive mindset with a passion for solving complex problems using data

Tech stack & tools:

• Python
• SQL
• AWS, GCP, Azure
• Snowflake, BigQuery, Redshift
• AI/LLM APIs
• Git

Nice to have:

• Experience with dbt, semantic layers, or modern data transformation tools
• Exposure to TypeScript
• Background in Bayesian modeling or marketing analytics (e.g. marketing mix modeling)
• Familiarity with experimentation frameworks (A/B testing, causal inference)
• Understanding of digital marketing ecosystems and attribution models

💡 This is an opportunity to work on high-visibility projects where your work will directly shape product strategy and business impact.