Full Stack AI/ML Engineer

Title - Full Stack AI/ML Engineer

REMOTE (EST and CST only)

EAD

CONTRACT TO HIRE

NEED GENUINE CANDIDATES WITH GENUINE ID/DL AND VISA THAT CAN CLEAR PERSONA ID VERIFICATION

NEED OLD AND EXCELLENT LINKEDIN WITH PROFILE PICTURE

Experience in regulated industries (healthcare, finance) with an understanding of data privacy and compliance requirements (HIPAA, SOC 2)

**MUST COMPLETE ROPES ASSESSMENT**

The project is building out the Chat system (Chat GPT) in NL. Ask a question and it queries the data on the network devices and pulls it in NL.  It will only be Network info, so a chat GPT just for networking teams.

No networking is a plus, like if they understand it but it''''''''s a developer role.

Will need to talk the talk but also walk it, meaning he will be having them show proof of knowledge in the interview. Write code for an example they give.

This is their 3rd attempt for this role. So he''''''''s going to be critical and particular.

Below is the JD hi whipped up while we were on the call..

Key Responsibilities

Application Development

Architect and develop end-to-end web applications using modern frontend and backend frameworks

Build and maintain RESTful and GraphQL APIs with a focus on performance, security, and reliability

Implement responsive, accessible UI components and design systems

Own the full software development lifecycle: design, implementation, testing, deployment, and monitoring

ML & AI Integration

Integrate machine learning models and AI services into production applications

Design and implement data ingestion pipelines, feature stores, and inference APIs

Collaborate with data scientists to operationalize models (MLOps), including versioning, monitoring, and retraining workflows

Build LLM-powered features including RAG (Retrieval-Augmented Generation), prompt engineering pipelines, and agentic workflows

Evaluate and adopt AI/ML frameworks and tooling (e.g., LangChain, LlamaIndex, Hugging Face, OpenAI/Anthropic APIs)

Infrastructure & DevOps

Build and maintain CI/CD pipelines for both application code and ML model deployments

Containerize services using Docker and orchestrate with Kubernetes

Contribute to infrastructure-as-code practices (Terraform, Helm)

Instrument applications with logging, metrics, and alerting (Grafana, Prometheus, Datadog)

Collaboration & Standards

Participate in design reviews, code reviews, and architectural discussions

Contribute to internal technical documentation and best practices

Mentor junior engineers and champion engineering quality across the team

Required Qualifications

5+ years of professional software development experience in full stack roles

Strong proficiency in at least one modern frontend framework: React, Vue, or Angular

Strong proficiency in at least one backend language/framework: Python (FastAPI/Django/Flask), Node.js, or Go

Solid understanding of relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis)

Hands-on experience integrating ML models or AI APIs into production systems

Familiarity with ML concepts: supervised/unsupervised learning, model evaluation, feature engineering

Experience with cloud platforms: AWS, Google Cloud Platform, or Azure — including managed ML services (SageMaker, Vertex AI, Azure ML)

Proficiency with Docker and container-based development workflows

Strong understanding of RESTful API design, authentication patterns (OAuth2, JWT), and API security

Experience with version control (Git) and collaborative development workflows

Experience building or fine-tuning LLMs or working with generative AI APIs (OpenAI, Anthropic, Cohere)

Familiarity with MLOps tooling: MLflow, Weights & Biases, Kubeflow, or equivalent

Experience with vector databases: Pinecone, Weaviate, Chroma, or pgvector

Knowledge of Kubernetes for deploying and scaling services

Background in data engineering: Spark, Airflow, dbt, or streaming systems (Kafka, Kinesis)

Contributions to open-source projects or published technical writing

Experience in regulated industries (healthcare, finance) with an understanding of data privacy and compliance requirements (HIPAA, SOC 2)