Machine Learning Engineer

Actalent - San Diego, CA

Full-time - Senior

San Diego, CA

10,001+ employees

Administrative and Support Services

About the position

Actalent is seeking a Machine Learning Engineer to join their team in San Diego, California. The role involves engaging with business teams to identify opportunities for AI and machine learning solutions, designing and deploying advanced models, and collaborating with engineers to implement scalable solutions. The engineer will also communicate insights and recommendations to partners and stay updated on the latest trends in AI and data engineering.

Responsibilities

• Engage deeply with business teams to identify opportunities and translate needs into AIML solutions.
• Design, build, and deploy state-of-the-art AIML models to solve complex business problems.
• Understand key performance levers and metrics to highlight AIML solution operational issues and drive improvement.
• Foster close collaboration with engineers and infrastructure partners to implement robust and scalable solutions.
• Communicate results and insights effectively to partners and leaders, providing clear and actionable recommendations.
• Stay updated with the latest trends, technologies, and best practices in AI and GenAI and data engineering.
• Regularly research and present new ideas to improve the team's technical capabilities.

Requirements

• 10+ years of industry experience with a BS in Computer Science or related field, or 5+ years with an MS/PhD.
• Expert in AIML modeling, Python, AIML Infrastructure, model deployment, and MLOps.
• Experience working in Supply Chain, Operations, or a related field.
• End-to-end GenAI application experience.
• Knowledge in RAG, Prompt Engineering, LoRA, and other GenAI techniques.
• Ability to operate independently and lead without authority.
• Superb communication and interpersonal skills.

Nice-to-haves

• Methodologies: Spiral, Agile, Waterfall, Lean.
• Programming Languages: C++, Python, Shell, SQL, R.
• IDE Tools: PyCharm, RStudio, Visual Studio Code, Jupyter Notebook, Google Collab, Navicat.
• ML Frameworks: Transformers, Scikit-Learn, Keras, TensorFlow, PyTorch, ONNX, NLTK, OpenAI, langchain.
• DL Architectures: LLM, ANN, CNN, R-CNN, RNN, GRU, LSTM, Transformers, Attention Mechanism, Tokenisers.
• Packages: Pandas, NumPy, Spark, Matplotlib, SciPy.
• Cloud Technologies: AWS, Azure, Digital Ocean, GCP, Paperspace.
• Database: MySQL, PostgreSQL, MongoDB, ChromaDB, Pinecone, SQLite.
• Web Frameworks and Deployment: Fast API, Flask, Nginx, Gunicorn, Uvicorn, Docker, Kubernetes.
• Miscellaneous Tools: JIRA, Auto Gluon, GitHub Actions, Datadog, MS Power BI, Postman, Locust, Streamlit, CUDA, cuDNN, TensorRT.
• Version Control: Git, GitHub, DVC.
• Operating Systems: Windows, Linux, Mac.