Senior Data Scientist with NLP

Stermedia; United States; Remote; USD 57,000 - 86,000; Full time

Benefits offered by this job

Flexible hours

Remote work

Self-development budget

MultiSport LuxMed

Team events

Job summary

Stermedia is seeking a skilled AI engineer to design and deploy end-to-end agentic AI solutions for clients, including academic collaborations. You will manage projects from client contact through production deployment, delivering scalable, secure systems across diverse domains.

You will implement agent orchestration, memory management, prompt engineering, and observability with Python, LangChain, and containerized deployments using Docker and Kubernetes.

Qualifications

• Strong proficiency in Python programming.
• Hands-on experience with Generative AI / LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel).
• Experience building end-to-end agentic solutions.
• Practical experience in agent development and orchestration.
• Expertise in prompt engineering and LLM optimization.
• Experience with container-based deployments (Docker, Kubernetes).
• Experience implementing agent observability (monitoring, tracing, evaluation).
• Knowledge of REST APIs and backend integration patterns.
• Experience deploying AI applications in cloud environments (AWS / Azure / GCP).
• Understanding of RAG architectures, embeddings, vector databases.

Responsibilities

• Design and develop end-to-end agentic AI solutions using modern LLM frameworks.
• Build and deploy Generative AI applications using Python.
• Develop and manage AI agents, including tool integrations, memory management, and reasoning workflows.
• Implement agent orchestration for multi-agent systems and complex task automation.
• Apply advanced prompt engineering techniques to optimize model performance.
• Establish agent observability frameworks (monitoring, tracing, logging, evaluation, guardrails).
• Deploy AI solutions using container-based architectures (Docker, Kubernetes).
• Ensure scalability, reliability, and security of AI systems in production.
• Integrate AI agents with enterprise APIs, databases, and external systems.
• Continuously evaluate model performance and implement optimization strategies.

Skills

Python

LLM frameworks

Agent development

Docker

Kubernetes

REST APIs

Cloud deployments

Observability

LangChain

LLamaIndex

Tools

LangChain

LlamaIndex

Semantic Kernel

TensorFlow/PyTorch

Job description

You’ll be working on diverse machine learning projects for local and international companies as well as in academic research. This will involve different phases of the end-to-end delivery – direct contact with the client, business analysis of the problem, coming up with an appropriate solution, implementation and moving it to the production environment.

Key Responsibilities

• Design and develop end-to-end agentic AI solutions using modern LLM frameworks
• Build and deploy Generative AI applications using Python
• Develop and manage AI agents, including tool integrations, memory management, and reasoning workflows
• Implement agent orchestration for multi-agent systems and complex task automation
• Apply advanced prompt engineering techniques to optimize model performance
• Establish agent observability frameworks (monitoring, tracing, logging, evaluation, guardrails)
• Deploy AI solutions using container-based architectures (Docker, Kubernetes)
• Ensure scalability, reliability, and security of AI systems in production
• Integrate AI agents with enterprise APIs, databases, and external systems
• Continuously evaluate model performance and implement optimization strategies

Required Skills & Qualifications

• Strong proficiency in Python programming
• Hands-on experience with Generative AI / LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, etc.)
• Experience building end-to-end agentic solutions
• Practical experience in agent development and orchestration
• Expertise in prompt engineering and LLM optimization
• Experience with container-based deployments (Docker, Kubernetes)
• Experience implementing agent observability (monitoring, tracing, evaluation frameworks)
• Knowledge of REST APIs and backend integration patterns
• Experience deploying AI applications in cloud environments (AWS / Azure / GCP)
• Understanding of RAG architectures, embeddings, vector databases

Preferred Qualifications

• Experience with multi-agent collaboration frameworks
• Experience with evaluation tools (e.g., prompt testing, hallucination detection, guardrails)
• Familiarity with MLOps practices
• Knowledge of distributed systems design
• Experience with real-time AI applications
• Background in machine learning fundamentals
• Communicative English – minimum C1 level

It is great if you have

• Experience with DevOps / MLOps tools and practices (e.g., Docker, Kubernetes, MLFlow, KubeFlow, DVC)
• Familiarity with a deep learning framework (Tensorflow, PyTorch)
• Experience in using additional data science related libraries (e.g., nltk, opencv, scikit-image, gensim, plotly, seaborn, xgboost, lightgbm)
• Strong general software development skills and knowledge of best practices
• Algorithmic and code optimization skills
• Knowledge of a cloud platform and experience in running cloud-based projects (GCP, AWS, Azure)

Salary: 20 000 - 30 000 PLN + VAT (B2B)

We offer you

• Working with the newest machine learning technologies
• Budget for self-development per year
• Possibility to contribute to a variety of interesting projects
• Internal workshops
• Personal branding (articles, conference speaker, internal workshop leader)
• Flexible work hours
• Remote work possibility
• Chillout room / free beverages / team & company events
• Friendly atmosphere
• MultiSport LuxMed