Machine Learning Engineer SFO, CA (Hybrid) at Jobisite / employment-usa.net

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Machine Learning Engineer SFO, CA (Hybrid)

at Jobisite in United States Of America

Machine Learning Engineer SFO, CA (Hybrid)
>
> Duration: 1+ year
>
> Job Description:
>
> NOTE : Must be good in comm and technical + Minimum of 8 years of work
> exp needed
>
> Role Overview
>
> We are seeking a skilled Machine Learning Engineer to design, develop,
> and deploy advanced AI/ML models, with a focus on Generative AI, RAG
> architectures, and large-scale machine learning applications. You will
> work on end-to-end ML pipelines, integrating state-of-the-art tools
> like OpenAI, Anthropic Claude, and vector databases to deliver
> high-quality solutions for real-world business challenges.
>
> Key Responsibilities
>
> · Machine Learning, Generative AI & RAG Development:
>
> · Build and fine-tune large language models (LLMs) using
> frameworks such as OpenAI GPT or Anthropic Claude.
>
> · Design and implement RAG pipelines for scalable, real-time
> applications leveraging vector databases like Pinecone, Weaviate,
> Opensearch.
>
> · Develop prompt engineering strategies to optimize model
> outputs for specific use cases.
>
> · Design and deploy scalable ML models that integrate with
> existing systems.
>
> · End-to-End ML Pipeline:
>
> · Architect, train, and deploy machine learning pipelines for
> NLP and multimodal AI solutions.
>
> · Conduct data preprocessing, feature engineering, and
> exploratory data analysis for training datasets.
>
> · Optimize embeddings for semantic search and document
> retrieval tasks.
>
> · Model Deployment & Optimization:
>
> · Deploy ML models in production environments using cloud
> platforms like AWS SageMaker, ECS or equivalent tools.
>
> · Ensure scalability, reliability, and low latency in
> production systems while monitoring model performance.
>
> · Implement CI/CD pipelines for ML models using Docker,
> Kubernetes, MLflow.
>
> · Ensure APIs and ML services handle high traffic with minimal
> latency.
>
> · Security & Compliance:
>
> · Ensure ML APIs follow best practices for authentication,
> authorization, and data privacy.
>
> · Collaboration & Integration:
>
> · Work closely with cross-functional teams including data
> scientists, software engineers, and product managers to align ML
> solutions with business objectives.
>
> · Work with data engineers to design feature stores and
> streaming pipelines.
>
> · Integrate ML outputs into enterprise systems while ensuring
> seamless user experiences.
>
> · Research & Innovation:
>
> · Stay updated on advancements in generative AI, LLMs,
> embeddings, and RAG technologies to enhance existing systems.
>
> · Experiment with new algorithms and frameworks to drive
> innovation in AI-powered applications.
>
> Required Skills & Qualifications
>
> Technical Expertise:
>
> · Minimum of 8 years of work experience with hast 4 years in
> Python; familiarity with frameworks like PyTorch, TensorFlow, and
> libraries like Hugging Face Transformers.
>
> · Hands-on experience with LLMs (e.g., OpenAI GPT models,
> Anthropic Claude) and fine-tuning techniques.
>
> · Strong understanding of RAG architectures and vector
> database integration (e.g., Opensearch, Pinecone, Weaviate).
>
> · API Development: FastAPI, Flask, Django
>
> · Containerization: Docker, AWS ECS, Kubernetes
>
> · Cloud & Data Tools:
>
> · Experience with cloud platforms such as AWS (SageMaker
> preferred), GCP Vertex AI, or Azure ML for deploying ML models.
>
> · Familiarity with SQL or NoSQL databases for data extraction
> and preprocessing tasks.
>
> · Problem-Solving Skills:
>
> · Ability to design scalable solutions for complex problems
> involving unstructured data and large datasets.
>
> · Strong analytical skills with a focus on optimizing ML
> workflows for performance and efficiency.
>
> Soft Skills:
>
> · Excellent communication skills to collaborate effectively
> with technical and non-technical stakeholders.
>
> · A passion for learning and staying ahead in the rapidly
> evolving field of artificial intelligence.
>
> Preferred Qualifications
>
> · Experience building conversational AI systems or chatbots
> using generative AI technologies.
>
> · Experience with building REST API using frameworks such as
> Fast API.
>
> · Experience with SQL and NoSQL database/store (Postgres,
> DynamoDB, Opensearch etc.)
>
> · Knowledge of NLP techniques such as sentiment analysis,
> topic modeling, or summarization tasks.
>
> · Familiarity with serverless architectures (e.g., AWS Lambda)
> or ECS for scalable ML deployment.
>
> · Bachelors or Masters degree in Computer Science, Data
> Science, Mathematics, or related fields.
Reference : Machine Learning Engineer SFO, CA (Hybrid) jobs

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