Particle41 is seeking an AI Engineer to design, develop, and deploy machine learning and deep learning models, including generative AI, while building scalable pipelines and collaborating with clients and data teams to deliver production-ready solutions. This is a remote role requiring a strong foundation in AI/ML and hands-on experience.
Responsibilities
- Lead end-to-end development of AI and ML models, from data ingestion and preprocessing through training, evaluation, deployment and monitoring.
- Design and implement generative AI solutions such as retrieval augmented generation, agentic workflows, MCP servers, and conversation AI agents aligned with business goals.
- Collaborate with data engineering teams to build and maintain data pipelines, feature stores, and orchestration frameworks.
- Develop and integrate AI models into production systems, including APIs, microservices, and cloud deployments.
- Optimize models and solutions for performance, scalability, robustness, and cost-efficiency.
- Monitor production performance for drift, bias, fairness, and reliability, and implement remediation when necessary.
- Document model design, experiments, data provenance, and solution rationale.
- Stay informed about the latest AI and ML research, frameworks, and tools such as LangChain, LangGraph, MCP clients/servers, Agents SDKs, and LiveKit, and propose innovative ideas.
- Engage directly with clients to understand problem statements, translate business requirements into AI solutions, and communicate results clearly.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- 3+ years of hands-on experience in AI and ML model development and deployment.
- Strong programming skills in Python and experience with major ML/AI frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, and LangGraph.
- Experience with vector databases (e.g., Pinecone, FAISS), retrieval augmented generation, and agentic workflows.
- Experience building or fine-tuning Large Language Models (LLMs).
- Experience deploying models to production, including building REST APIs, microservices, and monitoring solutions.
- Familiarity with Text-to-Speech and Speech-to-Text models or solutions (for example, Deepgram, ElevenLabs, Cartesia).
- Experience in computer vision, time-series modeling (ARIMA, Prophet), or multimodal AI.
- Familiarity with MLOps tools and frameworks such as MLflow, Kubeflow, and SageMaker.
- Strong understanding of algorithms, data structures, statistics, and core machine learning concepts (classification, regression, clustering, deep learning, sequence models).
- Ability to operate in a fast-paced, dynamic environment and adapt to changing priorities.
- Publications, open-source contributions, or personal AI/ML projects are a plus.
Technologies
- Python
- TensorFlow
- PyTorch
- scikit-learn
- LangChain
- LangGraph
- Pinecone
- FAISS
- MCP Clients/Servers
- Agents SDKs
- LiveKit
- MLflow
- Kubeflow
- SageMaker
- Deepgram
- ElevenLabs
- Cartesia
About Particle41
Particle41 anchors its work in the values of Empowering, Leadership, Innovation, Teamwork, and Excellence. These guiding principles form the ELITE framework that drives collaboration and outcomes for clients. We strive to empower individuals to reach their full potential, encourage initiative and guidance, foster creativity, promote empathetic teamwork, and pursue the highest quality in all endeavors.
Particle41 is committed to equal employment opportunities and to hiring based on merit and qualifications, without discrimination. We welcome applicants from diverse backgrounds who share our mission and values. We appreciate your interest and encourage applicants from these regions to apply. If you need assistance during the application or interview process, please contact careers@Particle41.com.
