Machine Learning Engineer – Generative AI

About ThinkTrends

ThinkTrends is an Enterprise AI company building secure, intelligent automation solutions for regulated and enterprise environments. Our platform enables organizations to deploy generative and agentic AI capabilities with a focus on control, compliance, and transparency.

We work with customers across the public sector and life sciences industry to modernize data workflows, streamline document processing, and deliver AI-driven decision support at scale. Our team brings together deep technical expertise and domain understanding to solve high-impact problems in complex, high-stakes environments.

Role Description

ThinkTrends is seeking a Machine Learning Engineer – Generative AI with 7 years of experience and passion for Agentic AI systems to join our growing team. In this role, you'll design, build, and deploy intelligent agents that can reason, plan, and take autonomous actions to solve complex problems. This is an excellent opportunity for engineers looking to work at the cutting edge of AI agent development while growing their skills in a supportive environment.

Key Responsibilities

Agentic AI Development

• Design and implement AI agents using Large Language Models (LLMs)
• Build multi-agent systems that can collaborate, communicate, and coordinate to achieve goals
• Develop reasoning and planning capabilities for autonomous decision-making
• Create tool-using agents that can interact with APIs, databases, and external systems
• Implement memory systems and context management for stateful agent interactions

Model Integration & Deployment

• Integrate various LLMs (GPT-4, Claude, Llama, etc.) into agent architectures
• Build and maintain agent orchestration pipelines and workflows
• Deploy agents to production environments with appropriate safety guardrails
• Monitor agent performance, behavior, and resource utilization
• Implement feedback loops for continuous agent improvement

Collaboration & Learning

• Work closely with senior engineers to design scalable agent architectures
• Participate in code reviews and contribute to best practices
• Document agent behaviors, architectures, and deployment processes
• Stay current with rapidly evolving agentic AI research and frameworks
• Contribute ideas for new agent capabilities and use cases

Required Qualifications

Education & Experience

• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
• 7 years of professional experience in machine learning, software engineering, or related role
• Demonstrated experience/interest in AI agents through projects, coursework, or professional work
• Experience building applications with LLMs or conversational AI systems

Technical Skills

• Programming: Strong proficiency in Python; comfortable with async programming
• LLM Integration: Hands-on experience with OpenAI API, Anthropic Claude, or similar LLM APIs
• Core ML: Understanding of machine learning fundamentals and model fine-tuning
• APIs & Integration: Experience building and consuming RESTful APIs
• Version Control: Proficient with Git and GitHub/GitLab workflows
• Databases: Working knowledge of SQL and vector databases (Pinecone, Weaviate, ChromaDB)

Core Competencies

• Understanding of prompt engineering and LLM optimization techniques
• Familiarity with Retrieval-Augmented Generation (RAG) patterns
• Basic knowledge of agent architectures (ReAct, Chain-of-Thought, Tree of Thoughts)
• Problem-solving mindset with attention to detail
• Strong communication skills and ability to work collaboratively
• Eagerness to learn and adapt in a fast-moving field
• Awareness of AI safety, ethics, and responsible AI practices

Preferred Qualifications

• Experience with agent evaluation and benchmarking
• Knowledge of reinforcement learning or RLHF concepts
• Familiarity with function calling and tool use in LLMs
• Experience with streaming responses and real-time agent interactions
• Understanding of multi-modal agents (text, vision, audio)
• Contributions to open-source agent projects or frameworks
• Experience with cloud platforms (AWS, GCP, Azure)
• Knowledge of containerization (Docker) and orchestration (Kubernetes)
• Familiarity with observability tools for LLM applications (LangSmith, Weights & Biases)

Technologies You'll Work With

• LLM Providers: OpenAI, Anthropic, Google, open-source models
• Vector Databases: Pinecone, Weaviate, ChromaDB, Qdrant
• Development Tools: Python, FastAPI, Git, Node.js
• Cloud Services: AWS/GCP/Azure (based on company infrastructure)
• Monitoring: LangSmith, Helicone, or similar LLM observability tools

Compensation & Benefits

• Competitive salary and benefits.
• Flexible hybrid work environment.
• Fast-paced, inclusive team culture focused on innovation and growth.
• Leadership opportunities in emerging AI and software innovation spaces.