AI/Machine Learning Engineer
Veritone · Irvine, CA · 2 mo ago
Engineering$175k/yrFull-time
About the Role
You will participate in building, documenting, and refactoring production-grade AI/ML pipelines, model integration layers, and scalable features that grow with business needs.
Responsibilities
- Identify and analyze areas in existing code, model inference workflows, and data pipelines for optimization, efficiency, and latency improvements.
- Partner with product, design, data, and infrastructure teams to integrate AI/ML capabilities and intelligent services into application workflows.
- Participate in on-call support rotation for production ML services, if necessary.
- Actively participate in team meetings: sharing knowledge on emerging AI trends, asking questions, and challenging assumptions.
- Help your team meet their commitments.
- Continuously improve your technical skills and stay current with rapid developments in the AI/ML landscape.
- Write maintainable code, including unit/integration tests, evaluation benchmarks, and readable code.
- Learn new frameworks, algorithms, and technical stacks quickly.
Requirements
- At least 3 years of professional experience building and deploying software systems, with direct experience integrating, fine-tuning, or operating AI/ML models in production environments.
- Deep proficiency with Python and standard ML libraries (e.g., PyTorch, NumPy, Pandas, Scikit-learn, Hugging Face).
- Hands-on experience with LLMs, RAG architectures, prompt engineering, or traditional ML model pipelines and inference serving.
- Ability to design and implement robust APIs and backend microservices in Python (bonus if experienced with Go or Node.js).
- Professional experience working with RDBMSs, NoSQL DBs, and Vector Databases.
- Demonstrated participation in the successful deployment, monitoring, and scaling of machine learning workloads and production code.
Skills
- AI/ML & Data: Python, PyTorch / TensorFlow, Hugging Face, LangChain / LlamaIndex, Vector DBs (e.g., Pinecone, Qdrant, pgvector)
- MLOps & Infrastructure: Docker, Kubernetes, MLflow / Weights & Biases, Cloud ML Platforms (AWS SageMaker, GCP Vertex AI, etc.)
- Backend & API: Python, Go, Node.js, GraphQL, ElasticSearch, and Postgres
Pay
The annual salary range for this position is $175,000 - $200,000, determined based on skills and experience comparable to the job requirements.
Benefits
- Eligibility for incentive compensation
- Health benefits
- Retirement benefits
- Life insurance
- Paid time off
- Parental leave and benefits
- Other employee perks and benefits