Entry-Level Machine Learning Engineer

Since 2010 , SynergisticIT has helped more than 10,000 jobseekers get hired at hundreds of tech clients by providing the required tech stack, real-world project experience, and U.S.-based exposure .

Role Description

Junior Machine Learning Engineer will be responsible for assisting in the creation, deployment, and monitoring of scalable ML models in production. Duties include data preprocessing, feature engineering, versioning ML models, and integrating machine learning components with live products. You will actively collaborate on project teams utilizing AWS Glue, Databricks, PySpark, TensorFlow, and Azure Data Lake, and contribute to code reviews and documentation tasks.

Required Skills

The role expects demonstrable familiarity with Python, cloud-based ML pipelines, and at least one framework among PyTorch, TensorFlow, or scikit-learn. Industry tools like Databricks for big data processing and Azure Data Lake for managing unstructured datasets are highly valued. Ability to work with code repositories (Git), conduct error analysis, and communicate findings in a business-friendly manner are required.

U.S. companies demand project-based evidence of your skills—real internship or portfolio work utilizing modern ML stacks makes you stand out.

Eligibility

Open to all those authorized to work in the U.S., including OPT and CPT visa holders.

Skills Development Path

If you're missing pieces of the ML and cloud deployment stack, the offers direct instruction and real project exposure in the precise technologies companies hire for. Supplement your journey with , , , and the .

SynergisticIT Client Network

SynergisticIT's connections to giants like Facebook, Google, Uber, Amazon, Apple, Twitter, JPMorgan, Walmart Labs, SAP, TCS, and Capgemini ensure broad exposure to high-impact ML roles. Participants secure salaries of $95K–$150K after placement.

Master both ML concepts and their real-world cloud deployment by leveraging SynergisticIT's industry-proven curriculum and client relationships, opening doors to the most in-demand U.S. ML engineering jobs.