Senior AI Engineer

Overview

On Site

Depends on Experience

Full Time

Skills

Python

TensorFlow

PyTorch

Keras

scikit-learn

Machine Learning

Deep Learning

Neural Networks

CNN

RNN

Transformers

Model Deployment

MLOps

MLflow

Kubeflow

Docker

Kubernetes

AWS

GCP

Azure

Data Preprocessing

Feature Engineering

Natural Language Processing (NLP)

Computer Vision

Generative AI

Large Language Models (LLMs)

Model Optimization

Statistics

Linear Algebra

Probability

Cloud AI Services

Data Pipelines

Real-time Inference Systems

Technical Leadership

Code Review

Cross-functional Collaboration

Job Details

Job Title: Senior AI Engineer
Location: Fremont

About the Role

We are seeking a highly skilled and experienced Senior AI Engineer to join our growing team. In this role, you will lead the design, development, and deployment of advanced AI/ML solutions that power our core products and services. You will work closely with data scientists, engineers, and product stakeholders to solve complex business problems using state-of-the-art AI technologies.

Key Responsibilities

Lead the development and deployment of scalable AI/ML models across various domains (e.g., NLP, computer vision, predictive analytics)
Collaborate with cross-functional teams to define AI strategies, architecture, and implementation roadmaps
Design and optimize deep learning architectures (CNNs, RNNs, Transformers) for real-world applications
Own the full AI model lifecycle: data collection, preprocessing, training, validation, deployment, and monitoring
Ensure high-quality code through code reviews, testing, and documentation
Mentor junior engineers and contribute to building a culture of innovation and technical excellence
Evaluate and integrate emerging AI technologies and frameworks into the existing tech stack

Required Qualifications

Bachelor's or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field (Ph.D. preferred)
Minimum 7+ years of experience in AI/ML development, with proven production-level deployment expertise
Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn
Deep understanding of machine learning algorithms, deep learning models, and model evaluation techniques
Experience with Docker, Kubernetes, and deploying AI models on cloud platforms (AWS, Google Cloud Platform, or Azure)
Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow)
Strong mathematical background in linear algebra, probability, statistics, and optimization
Excellent communication and leadership skills, with a track record of mentoring and team collaboration

Preferred Qualifications

Experience in Generative AI, Large Language Models (LLMs), or multi-modal AI systems
Familiarity with data lake architecture, data pipelines, and real-time inference systems
Contributions to open-source AI projects or publications in peer-reviewed journals

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