Description:

As an AI Engineer at Particle41, you will design, develop, and deploy machine-learning and deep-learning models/solutions, including generative-AI, to address complex business problems.
You will collaborate with data scientists, data engineers, software engineers, and client stakeholders.
Your responsibilities will include leading the end-to-end development of AI/ML models, from data ingestion and preprocessing to model training, evaluation, deployment, and monitoring.
You will build generative-AI solutions aligned with business goals, such as RAG, Agentic Workflows, MCP Servers, and Conversation AI Agents.
You will work closely with data engineering teams to build and maintain data pipelines, feature stores, and orchestration frameworks.
You will develop and integrate AI models into production systems, including APIs, microservices, and cloud deployments.
Your role will involve optimizing models and solutions for performance, scalability, robustness, and cost-efficiency.
You will monitor the performance of models and solutions in production, addressing issues such as drift, bias, fairness, and reliability.
You will document model design, experiments, data provenance, and solution rationale.
Staying updated on the latest AI/ML research, frameworks, and tools, you will propose innovative ideas.
You will work directly with clients to understand problem statements, translate business requirements into AI solutions, and communicate results clearly.

Requirements:

A Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field is required.
You must have 3+ years of hands-on experience in AI/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 are essential.
Experience with vector databases like Pinecone and FAISS, as well as RAG and Agentic workflows, is required.
You should have experience building or fine-tuning Large Language Models (LLMs).
Experience in deploying models into production, including building REST APIs and microservices, is necessary.
Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, and Cartesia is preferred.
Experience in computer vision, time-series modeling (ARIMA, Prophet), or multimodal AI is a plus.
Familiarity with MLOps tools and frameworks such as MLflow, Kubeflow, and SageMaker is required.
A strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals is essential.
You must be able to work in a fast-paced, dynamic environment and adapt to changing priorities.
Publications, open-source contributions, or personal projects in the AI/ML domain are valued.

Particle41 is committed to empowering individuals to reach their full potential and provides a supportive work environment.
The company values leadership, innovation, teamwork, and excellence, fostering a culture that encourages creativity and collaboration.
Particle41 offers equal employment opportunities to all employees and applicants, ensuring a diverse and inclusive workplace.
The company is dedicated to providing assistance during the application or interview process for those who need it.

Skills