Machine Learning Engineer New Graduate

Machine Learning Engineer — New Graduate

Location: San Francisco Bay Area, CA

Employment Type: Full-Time

Experience Level: New Graduate / 0–2 Years

About the Role

We are seeking a motivated Machine Learning Engineer to join our AI and engineering team on a full-time basis. This role is designed for recent graduates who are passionate about machine learning, AI systems, and building production-ready ML applications.

You will work across the ML lifecycle, from data preparation and model development to training, evaluation, deployment, and monitoring. You will collaborate closely with AI researchers, software engineers, and product teams to turn machine learning models into reliable production systems.

Key Responsibilities

* Develop, train, evaluate, and deploy machine learning models.

* Build scalable machine learning pipelines for data processing, training, evaluation, and inference.

* Work with large datasets to perform feature engineering, data preprocessing, and quality validation.

* Implement and optimize models using PyTorch, TensorFlow, scikit-learn, or similar frameworks.

* Develop production ML inference services and integrate models into software applications.

* Build evaluation frameworks to measure model accuracy, robustness, latency, and reliability.

* Optimize model performance, inference speed, and resource utilization.

* Develop and maintain MLOps infrastructure, including model versioning, experiment tracking, CI/CD, and monitoring.

* Collaborate with AI researchers to productionize research models and experimental prototypes.

* Work with software engineers to design scalable APIs and distributed ML systems.

* Monitor deployed models and investigate performance degradation and data distribution changes.

* Research and evaluate new ML techniques, frameworks, and infrastructure technologies.

Qualifications

* Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Statistics, Mathematics, Electrical Engineering, or a related technical field.

* Recent graduate or graduating student with 0–2 years of professional experience.

* Strong programming skills in Python.

* Strong understanding of:

    * Machine learning algorithms

    * Deep learning

    * Probability and statistics

    * Linear algebra

    * Optimization

    * Data structures and algorithms

* Experience with PyTorch, TensorFlow, scikit-learn, or similar ML frameworks.

* Experience developing ML models through coursework, research, internships, or independent projects.

* Strong software engineering and problem-solving skills.

Preferred Qualifications

* Experience with LLMs, generative AI, NLP, computer vision, or reinforcement learning.

* Experience with Hugging Face, Transformers, embeddings, RAG, or AI agents.

* Familiarity with Docker, Kubernetes, AWS/GCP/Azure, or GPU computing.

* Experience with MLflow, Weights & Biases, Ray, Kubeflow, or similar ML infrastructure.

* Experience building REST APIs or production ML inference services.

* Familiarity with SQL, PostgreSQL, Redis, Kafka, or distributed data processing.

* Experience with model optimization, quantization, distributed training, or inference acceleration is a plus.

* Open-source contributions, research projects, Kaggle competitions, or significant ML projects are a plus.

What We Offer

* Opportunity to build production machine learning systems from end to end.

* Exposure to modern AI, LLM, and ML infrastructure technologies.

* Close collaboration with AI researchers and experienced software engineers.

* Ownership of meaningful projects spanning research and production.

* A technically challenging and intellectually rigorous environment.

* Competitive compensation and performance-based incentives.

* Full-time career development opportunities within the AI and engineering teams.

Equal Opportunity

We are committed to providing equal employment opportunities to all qualified candidates. We value diversity of background, perspective, and experience and encourage candidates from all technical disciplines to apply.