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About the role:
Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises.
Required skills
Roles & Responsibilities
Advantages of joining Turing:
Don't meet every single requirement Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Job ID: 126898303
Skills:
data pipeline, API design, Tensorflow, Pytorch, Docker, Python, AWS, Gcp, Azure, Kubernetes, CI CD for AI, Pinecone, backend systems, Mistral, Distributed microservices, model monitoring, LangChain, LLaMA, LLMs, Anthropic, FAISS, xVector DBs, RAG, drift detection, Milvus, OpenAI, Weaviate
Skills:
Adf, Agentic AI, algorithms for generative models, generative models, GenAI systems
Skills:
Machine Learning, Artificial Intelligence, Google Cloud, Tensorflow, Deep Learning, Docker, Pytorch, Keras, Python, AWS, GANs, LLMs, cloud platforms, Generative Models, Transformers, Generative AI models
Skills:
Sql, Django, REST, Flask, Swagger, Postgres, Redis, FastAPI, Kubernetes, Python, Azure, Restful Apis, attention tokens, context window, AIML, Core AI, LLM behavior, data processing pipelines, MCP, RAG, automation testing frameworks, operational monitoring, Llm, Transformers, OpenAPI, model evaluation procedures, MCP Model Context Protocol, observability, FastMCP, Docket
Skills:
Kubernetes, Databricks, MLops, Python, Docker, Apis, REST, Azure ML, Lang Chain, GenAI applications, Monitoring, Lang Graph, observability, Azure AI, real-time workflows, batch inference
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