Machine Learning Engineer

W2 only

Duration - 6 months Contract to hire

Location - 100% remote - PST hours

JOB DESCRIPTION

Seeking an experienced Machine Learning Engineer to join our team and play a pivotal role in the development of our advanced Generative AI applications and systems. This dynamic role involves a variety of initiatives, including designing, building, and delivering ML applications leveraging AI technologies like LLMs and FMs.

Key Responsibilities:

• Develop, train, and fine-tune ML models, with a focus on LLMs, FMs, and RAG.
• Lead the model development lifecycle from data collection and preprocessing to model evaluation and deployment.
• Collaborate with business partners, engineers, analysts, and data scientists to translate business requirements into effective AI solutions.
• Conduct experiments, including A/B testing, to enhance model accuracy and efficiency.
• Deploy models to production, ensuring scalability and efficiency.
• Optimize machine learning applications for performance and reliability.
• Monitor and maintain models in production environments.
• Stay updated on AI, ML, and GenAI advancements to drive innovation.
• Provide data-driven insights and recommendations.
• Mentor team members on AI/ML engineering best practices

Must Haves:

• 5+ years of full-time work experience in one or more relevant machine-learning roles.
• Proven experience as a Machine Learning Engineer or in a similar role.
• Experience with developing machine learning models at scale from inception to business impact
• Strong expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R).
• Experience in working with large data sets, data processing, and data analytics.
• Familiarity with cloud platforms, preferably AWS, and their machine learning services.
• Strong problem-solving skills and ability to work in a fast-paced, team-oriented environment.
• Excellent communication and collaboration skills.
• Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related field.

Preferred Qualifications:

• Experience delivering models through the MLOps life cycle from exploration to serving.
• Familiarity with GenAI technology stack, including frameworks for prompt engineering, guardrails for GenAI applications, and LLM fine-tuning.
• Experience working with VectorDBs and other data infrastructure required to efficiently support Generative AI training pipelines and production applications.