Machine Learning Engineer

About Infostrux:

Infostrux is one of North America's fastest-growing data-focused consultancies. Within 18 months of our founding in 2021, Snowflake recognized us at the highest partnership tier—a reflection of our deep expertise and impact.

We help organizations unlock the value of their data by building modern, cloud-native platforms that power analytics, AI, and machine learning. Our work spans the modern data stack—covering data engineering, architecture, integration, and modelling with Snowflake as one of our core partners.

From startups to Fortune 500s across industries like finance, health, gaming, and retail, we design and deliver scalable data solutions that enable faster, smarter, data-driven decisions. And as proud recipients of the Great Place to Work® Certification (2025), we are equally committed to fostering a culture of trust, collaboration, and growth for our people.

Job Summary:

As a Machine Learning Engineer, you will help design, build, and deploy machine learning solutions that support real-world business needs. Working closely with senior engineers, data teams, and analysts, you will contribute to model development, data pipelines, and machine learning operations while gaining hands‑on experience with modern cloud and data platforms. This role is ideal for someone who loves solving practical problems with machine learning, is eager to grow in machine learning operations, and thrives in collaborative, technical environments.

What you'll get to do:

• Model Development & Implementation: Build and train machine learning models based on project requirements, supporting model evaluation, validation, and performance improvements.
• Data Pipeline Support: Develop and maintain data preprocessing workflows and feature pipelines to ensure seamless data processing. Ensure data quality and consistency across ML systems.
• Machine Learning Operations & Deployment: Contribute to ML deployment pipelines, model versioning, and monitoring. Collaborate with senior engineers on CI/CD and automation practices.
• Cloud & Data Integration: Work with cloud platforms (AWS, Azure, GCP) and Snowflake to operationalize Machine Learning models. Integrate Machine Learning components with modern data architecture.
• Collaboration: Partner with data engineers, analysts, and senior ML engineers to translate business needs into technical solutions. Support documentation, testing, and reliability efforts

What you'll bring:

• Strong foundation in machine learning fundamentals
• Proficiency in Python and common ML libraries (pandas, scikit‑learn, PyTorch or TensorFlow)
• Experience in training and evaluating ML models
• Exposure to cloud platforms (AWS, Azure, or GCP)
• Familiarity with MLOps concepts such as model tracking, automated pipelines, and monitoring

Additional Assets:

• Basic understanding of containerization (Docker or Kubernetes)
• Experience working with APIs or production data workflows
• Interest in responsible AI, security, or governance

What we work with:

• Machine Learning: pandas, scikit‑learn, PyTorch
• MLOps: MLflow, Langchain, Langflow, Airflow
• Data: Snowflake, Databricks Lakehouse
• Cloud: AWS, GCP, Azure
• Infra & Orchestration: Docker, Kubernetes, ECS, Terraform
• Languages: Python (primary), SQL

What's in it for you? We're so glad you asked

You will be surrounded by some of the brightest and most accomplished technical minds in our field. We are a team of very diverse and passionate professionals who love working together and solving problems by leveraging technology to help our customers. We pride ourselves in our outstanding work culture that is grounded in our 8 core values: trust, excellence, integrity, humility, accountability, responsibility, kindness, and fun.

We value our people above all, and we provide a competitive compensation and benefits package to show our team our appreciation for everything they do:

• We are a 100% remote organization and our team members can work from the comfort of their homes, as well as anywhere abroad where they are entitled to work for up to 3 months per year.
• We are strong believers of work‑life integration and we offer a flexible schedule so that our team can manage their own workload and still be there for family and loved ones.
• We offer 4 weeks of vacation annually, in addition to paid personal and sick days, so that our team can unwind, recharge, and enjoy time away for hobbies and family.
• We provide a monthly bring-your-own-device allowance for each team member to choose the computer and phone of their preference (and it is t