Asks for

The ad says“Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows.”
The ad says“Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models).”
The ad says“Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI.”
The ad says“Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, Cartesia etc.”
The ad says“Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI.”
The ad says“Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models).”
The ad says“Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, Cartesia etc.”
The ad says“Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, Cartesia etc.”
The ad says“Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows.”
The ad says“Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).”
The ad says“Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).”
The ad says“Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).”
The ad says“Experience building or fine-tuning Large Language Models (LLMs).”
The ad says“Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models).”
The ad says“Experience deploying models into production: building REST APIs, microservices and monitoring.”
The ad says“Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).”
The ad says“Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).”
The ad says“Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows.”
The ad says“Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI.”
The ad says“Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).”
The ad says“Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).”
The ad says“Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows.”
The ad says“Experience deploying models into production: building REST APIs, microservices and monitoring.”
The ad says“Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).”
The ad says“Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).”
The ad says“Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models).”
The ad says“Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).”
The ad says“Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI.”
The ad says“Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows.”

AI Engineer

Role Overview:

As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively.

In This Role, You Will:

Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring.
Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals.
Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks.
Develop and integrate AI models into production systems (APIs, microservices, cloud deployments).
Optimize models/solutions for performance, scalability, robustness and cost-efficiency.
Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation.
Document model design, experiments, data provenance and solution rationale.
Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas.
Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results.

Skills and Experience We Value:

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
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 (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).
Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows.
Experience building or fine-tuning Large Language Models (LLMs).
Experience deploying models into production: building REST APIs, microservices and monitoring.
Familiarity with Text-to-Speech and Speech-to-Text models/solutions like Deepgram, ElevenLabs, Cartesia etc.
Experience in computer vision, time-series modelling (ARIMA, Prophet) or multimodal AI.
Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).
Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification, regression, clustering, deep learning, sequence models).
Ability 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

About Particle41

Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence ( ELITE )

E - Empowering: Enabling individuals to reach their full potential. L - Leadership: Taking initiative and guiding each other toward success. I - Innovation: Embracing creativity and new ideas to stay ahead. T - Teamwork: Collaborating with empathy to achieve common goals. E - Excellence: Striving for the highest quality in everything we do.

We seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values. We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring.

We appreciate your interest and encourage applicants from these regions to apply. If you need any assistance during the application or interview process, please feel free to reach out to us at careers@Particle41.com.