20 of 20 Pinecone Jobs in the South East

QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming & APIs: Expert-level Python and demonstrable experience building production services with FastAPI. Cloud Platform: Mastery of GCP, particularly Vertex AI, Google Kubernetes Engine (GKE More ❯

QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming & APIs: Expert-level Python and demonstrable experience building production services with FastAPI. Cloud Platform: Mastery of GCP, particularly Vertex AI, Google Kubernetes Engine (GKE More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development of a strategic AI adoption roadmap More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and vector databases (e.g. Pinecone, FAISS, Weaviate). Proficiency in Python plus at least one other backend language (TypeScript or Java preferred). Proven experience with AWS , containerisation, and infrastructure as code (Terraform, Docker). More ❯

Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar systems, we’d love More ❯

Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar systems, we’d love More ❯

Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar systems, we’d love More ❯

influenced ARR aligned with GTM metrics. Required Qualifications 5+ years in AI/ML engineering, applied AI, or solutions engineering roles. Proven experience with: RAG pipelines (LangChain, LlamaIndex, Weaviate, Pinecone, Milvus, etc.) Fine-tuning LLMs (LoRA, PEFT, instruction-tuning, domain adaptation) Deploying inference endpoints at scale (Triton, HuggingFace Inference, Ray Serve, Kubernetes) Strong coding skills in Python (and ideally one More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

as Python, Java, Go, or similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc.) or database internals. Proven More ❯

in data engineering, ML engineering, or similar technical roles Strong Python skills and comfort working across complex ingestion workflows Experience managing NoSQL and vector databases at scale (MongoDB, Weaviate, Pinecone, etc.) Solid understanding of modern data pipeline tools (Airflow, Prefect, Dagster) Practical experience with LLM development, embeddings, and RAG architectures Familiarity with distributed systems and cloud platforms (AWS, GCP, or More ❯

from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and shape the product roadmap. An environment … Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure, Transformers, Reinforcement Learning, Vector Databases, Pinecone, Weaviate, Semantic Search, API Development, AI Deployment, Model Serving, AI Automation, Early Stage Startup, AI Startups, Tech Startup, Machine Intelligence, Applied AI, AI Applications, AI Innovation, AI Product Development, AI More ❯

end frameworks (e.g. React, Next.js, React Native) and back-end systems (e.g. Node.js, Python). AI integrations: Hands-on experience integrating AI tools and services (e.g. OpenAI, Anthropic, LangChain, Pinecone, speech/video APIs). Prototype mindset: You've built MVPs in fast-moving environments and are comfortable with ambiguity. Cloud/data experience: Familiar with AWS, GCP, or Firebase More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look, not just how they run) Comfort building MVPs that can More ❯

z2bz0 years of experience in full stack development (React + Node or equivalent stack) Experience integrating and fine-tuning LLMs, embeddings, or vector search (e.g. OpenAI, LangChain, Pinecone, Lovable and Google’s Agent Development Kit or equivalent vide coding platforms) Strong frontend sensibility (you care how things feel and look, not just how they run) Comfort building MVPs that can More ❯