Position Overview

We are seeking an experienced AI Engineer to join our dynamic startup team and drive innovative artificial intelligence solutions from conception to production deployment. This role is perfect for a seasoned professional who thrives in fast-paced environments and wants to make a significant impact on cutting-edge AI products that serve enterprise and consumer markets.

Key Responsibilities

Core AI Development

Algorithm Development & Implementation: Design, develop, and optimize machine learning models and AI algorithms using Python, TensorFlow, PyTorch, and other modern ML frameworks

Model Training & Fine-tuning: Build and train models on large datasets, including experience with Large Language Models (LLMs), transformers, and generative AI applications

Data Pipeline Management: Construct robust data pipelines using tools like Apache Spark, Hadoop, and cloud platforms for efficient data processing and model training

Natural Language Processing: Develop advanced NLP solutions including sentiment analysis, text classification, named entity recognition, and conversational AI systems

Production & Deployment

MLOps Implementation: Deploy machine learning models to production environments using Docker, Kubernetes, and CI/CD pipelines

Cloud Infrastructure: Leverage AWS, Azure, or Google Cloud Platform for scalable AI solution deployment and management

Model Monitoring: Implement comprehensive monitoring, A/B testing, and performance optimization systems for production models

API Development: Create robust APIs for model integration with existing applications and third-party systems

Collaboration & Leadership

Cross-functional Collaboration: Work closely with product managers, data scientists, and engineering teams to align AI solutions with business objectives

Technical Communication: Explain complex AI concepts to non-technical stakeholders and contribute to technical documentation

Code Quality: Write clean, maintainable, and well-documented code following software engineering best practices

Innovation: Stay current with latest AI research, implement novel techniques, and contribute to the company's AI strategy

Required Qualifications

Technical Skills

Programming Proficiency: 5+ years of experience with Python; familiarity with R, Java, or C++ preferred

Machine Learning Expertise: Deep understanding of supervised/unsupervised learning, deep learning, neural networks (CNNs, RNNs, Transformers)

Framework Experience: Hands-on experience with TensorFlow, PyTorch, Keras, scikit-learn, and Hugging Face

Data Management: Proficiency with SQL, NoSQL databases, and big data technologies (Spark, Kafka)

Cloud Platforms: Production experience with AWS, Azure, or GCP services including SageMaker, ML Engine, or Azure ML

Mathematical & Statistical FoundationAdvanced Mathematics: Strong background in linear algebra, calculus, statistics, and probability theory

Statistical Modeling: Experience with hypothesis testing, regression analysis, and experimental design

Optimization Techniques: Knowledge of hyperparameter tuning, regularization, and modeloptimization strategies

**DevOps & Engineering

Containerization: Experience with Docker and container orchestration using Kubernetes

Version Control: Proficiency with Git, GitOps practices, and collaborative development workflows

CI/CD Pipelines: Hands-on experience building automated testing and deployment pipelines**Infrastructure as Code: Familiarity with Terraform, CloudFormation, or similar IaC tools

*Preferred Qualifications*

*Advanced Experience*

Industry Experience: 5-8 years in AI/ML engineering roles, preferably with startup or fast-growing company experience

Domain Expertise: Experience in specific domains like computer vision, NLP, recommendation systems, or generative AI

Research Background: Publications in AI/ML conferences or contributions to open-source projects

Leadership Experience: Previous experience mentoring junior engineers or leading technical initiatives

*Specialized Skills*

Generative AI: Experience with GPT models, LLaMA, fine-tuning techniques, and prompt engineering

Computer Vision: Expertise in image processing, object detection, and computer vision pipelines

MLOps Tools: Familiarity with Kubeflow, MLflow, Weights & Biases, or similar model lifecycle management tools

Data Engineering: Experience with real-time data processing and streaming architectures

*Education Requirements*

Bachelor's Degree in Computer Science, Mathematics, Statistics, Data Science, or related technical field

Advanced Degree Preferred: Master's or PhD in AI, Machine Learning, or related field provides competitive advantage

Alternative Pathways: Equivalent practical experience with strong portfolio of AI projects will be considered

*Compensation Package*

Salary ExpectationsBase Salary Range: $147,000 - $268,000 annually, depending on experience and location

Geographic Variations: San Francisco Bay Area and NYC command premium rates of 15-25% above national average

*Equity & Benefits*

Equity Participation: Significant equity package with potential for substantial long-term gains

Benefits Package: Comprehensive health insurance, 401(k) matching, professional development allowance

Remote Work Options: Flexible remote work arrangements with occasional on-site collaboration

Learning & Development: Conference attendance, certification support, and continuous learning opportunities