Particle41 is seeking an AI Engineer to design, develop, and deploy machine-learning and deep-learning models, including generative AI, while building scalable data pipelines and partnering with clients and data teams to deliver production-ready solutions. This remote role sits at the intersection of cutting-edge AI techniques and tangible business outcomes, offering opportunities to shape how clients leverage analytics across industries.
Responsibilities
- Oversee the full lifecycle of AI and ML models, from data ingestion and preprocessing through training, evaluation, deployment, and ongoing monitoring.
- Develop generative AI solutions including retrieval augmented generation (RAG), 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.
- Integrate AI models into production systems via 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, implementing remediation as needed.
- Document model designs, experiments, data provenance, and solution rationale.
- Stay informed on the latest AI/ML research, frameworks, and tools (including LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit) and propose innovative ideas.
- Engage directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
- Minimum 3 years of hands-on AI/ML model development and deployment experience.
- Strong Python programming skills and experience with major ML/AI frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, and LangGraph.
- Experience with vector databases (Pinecone, FAISS), RAG, and agentic workflows.
- Experience building or fine-tuning large language models (LLMs).
- Proven track record deploying models to production, including REST APIs, microservices, and monitoring.
- Familiarity with Text-to-Speech and Speech-to-Text technologies (e.g., Deepgram, ElevenLabs, Cartesia).
- Experience in computer vision, time-series modeling (ARIMA, Prophet), or multimodal AI.
- Understanding of MLOps tools and frameworks (MLflow, Kubeflow, SageMaker).
- Strong foundation in algorithms, data structures, statistics, and core machine-learning principles (classification, regression, clustering, deep learning, sequence models).
- Ability to thrive in a fast-paced, dynamic environment with changing priorities.
- Publications, open-source contributions, or personal AI/ML projects.
Technologies
- Python
- TensorFlow
- PyTorch
- scikit-learn
- LangChain
- LangGraph
- Pinecone
- FAISS
- MCP Clients/Servers
- Agents SDKs
- LiveKit
- MLflow
- Kubeflow
- SageMaker
- Deepgram
- ElevenLabs
- Cartesia
About Particle41
Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence guide how we work with clients to achieve outcomes. We embody these values as part of the ELITE framework, which stands for Empowering, Leadership, Innovation, Teamwork, and Excellence. We seek team members who embody these values and contribute to our mission. Particle41 provides equal employment opportunities to all applicants and employees, with decisions based on merit and qualifications and without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, or protected status. We welcome applicants from diverse backgrounds and regions to apply. If you need assistance during the application or interview process, please contact careers@Particle41.com.
