Senior AI Engineer

Synergy Interactive; Chicago (IL); On-site; USD 160,000 - 220,000; Full time

Job summary

Synergy Interactive is seeking a Senior AI Engineer in Chicago, focusing on integrating and optimizing AI systems. This challenging role involves defining intelligence within their platform, requiring expertise in machine learning, backend architecture, and real-time inference. The ideal candidate will have solid programming skills and experience with AI deployments, working collaboratively to drive impactful solutions.

Qualifications

• 3–5 years of experience in software engineering with strong backend fundamentals.
• Solid programming skills in Python; familiar with Go, Rust, or TypeScript.
• Experience deploying models in production via various platforms.

Responsibilities

• Integrate and operationalize AI models for various tasks.
• Design scalable APIs to support low-latency inference.
• Collaborate with product and research teams for effective AI application.

Skills

Programming in Python

Backend Engineering

AI System Integration

Tools

AWS SageMaker

TensorFlow

PyTorch

Job description

This range is provided by Synergy Interactive. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$160,000.00/yr - $220,000.00/yr

About the Role:

Looking for a Senior AI Engineer to define how intelligence is embedded at the core of our platform. This is a deeply technical, high-impact role at the intersection of applied machine learning, infrastructure, and product. The work is not theoretical. It is production focused, system-minded, and grounded in real use.

This engineer will lead the integration and optimization of advanced AI systems, with a focus on large language models, powering core features across classification, retrieval, summarization, and generation. From backend architecture to real-time inference, they will build systems that are fast, reliable, and measurable. The role blends strategic thinking with deep technical execution.

The Senior AI Engineer will own the full lifecycle of AI features—from model selection and tuning to deployment and evaluation. They will partner with research, product, and platform teams to identify high-leverage applications of machine learning and deliver real impact. Internal tooling, monitoring, and observability will be central to their approach, ensuring performance that is both scalable and trusted.

This role is built for someone who leads with precision, thinks in systems, and thrives in complexity. Here, intelligence is not an add-on. It is foundational—and this role is key to making that foundation performant, resilient, and evolving.

Key Responsibilities:

• Integrate and operationalize AI models for classification, ranking, retrieval, summarization, or generation tasks.

• Design and build scalable APIs and infrastructure to support low-latency, high availability inference (e.g., using Docker, FastAPI, or gRPC).

• Optimize inference performance across latency, cost, and accuracy dimensions.

• Collaborate with product and research teams to identify opportunities to apply AI effectively.

• Contribute to internal tools, model evaluation pipelines, and monitoring systems.

• Stay current on AI trends, tooling, and best practices, especially around LLMs and applied ML.

Required Qualifications:

• 3–5 years in software engineering, with strong backend fundamentals.

• Solid programming skills in Python (bonus: experience with Go, Rust, or TypeScript).

• Familiarity with RAG, vector databases, and embedding-based search techniques.

• Proficiency with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or LangChain.

• Experience deploying, serving, or embedding models in production (e.g., via AWS SageMaker, Vertex AI, or custom solutions).

• Strong understanding model performance trade-offs (latency, throughput, accuracy, cost).

• Comfort working with RESTful APIs, CI/CD pipelines, and cloud platforms (AWS preferred).

• Take ownership of projects and make critical decisions when necessary.

• Must be willing and able to work on-site at our Chicago office.

Preferred Qualifications:

• Experience with LLM fine-tuning, prompt engineering, or system-level RAG optimizations.

• Knowledge of MLOps best practices and tools (e.g., MLflow, Weights & Biases, Airflow).

• Contributions to open-source AI/ML projects.

• Exposure to agent frameworks like LangGraph, Autogen, or Eino.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Industries

  Technology, Information and Media and Engineering Services

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