Machine Learning Engineer

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Responsibilities

The Opportunity:

The AI/ML Architect is responsible for designing, developing, and implementing advanced AI-driven conversational and agentic solutions using Azure, AWS or custom developed AI services, cutting-edge language models, and modern programming languages such as Python and Java. This role demands deep expertise in natural language processing (NLP), dialog management, agent orchestration, and cloud-native AI deployments to create seamless, intelligent, and scalable conversational experiences and autonomous agents.

Your Impact:

As AI/ML Architect - Conversational and Agentic AI your functions would consist of

1. Conversational & Agentic AI Solution Architecture & Design:

• Design and architect end-to-end conversational AI systems, including chatbots, voice assistants, and intelligent agents, leveraging advanced NLP techniques and large language models (LLMs).

• Develop comprehensive dialog flows, intent recognition models, entity extraction, and sentiment analysis for complex conversational interactions.

• Architect agentic systems, focusing on planning, reasoning, and execution, integrating tools and APIs for autonomous task completion.

• Define the architecture for integrating conversational and agentic AI with enterprise systems and external APIs.

• Create detailed technical specifications and documentation for conversational and agentic AI solutions.

1. Cloud & Infrastructure Development (Focused on Conversational & Agentic AI):

• Design and deploy scalable and resilient cloud infrastructure for conversational and agentic AI applications on Azure or AWS, leveraging Native AI services, Azure CoPilot Studio or AWS Lex & Connect, Azure ML / AWS Sagemaker, and LLM services like OpenAI / Bedrock.

• Design and deploy multiple AI Agents using Open Source development, deployment and orchestration frameworks like LangGraph and or their commercial equivalent.

• Optimize cloud resources for efficient processing of natural language queries, LLM inferences, and agentic workflows.

• Implement serverless architectures and containerized solutions (Docker, Kubernetes) for deploying and managing conversational and agentic AI models.

1. Database & Knowledge Engineering (Focused on Conversational & Agentic AI):

• Design and implement knowledge graphs and vector databases (e.g., Azure Cognitive Search, Pinecone, Weaviate) to support conversational and agentic AI systems.

• Develop data pipelines for ingesting, processing, and storing conversational data, including transcripts, user interactions, and knowledge base content.

• Implement data retrieval and augmentation strategies, including Retrieval Augmented Generation (RAG) to enhance the accuracy and relevance of conversational and agentic responses.

1. Integration & Deployment (Focused on Conversational & Agentic AI):

• Integrate conversational and agentic AI solutions with various channels, including web, mobile, messaging platforms (SMS, WhatsApp, etc.), Social Media (Facebook Messenger, Ticktock, etc.) and voice interfaces.

• Develop APIs and microservices for seamless integration with enterprise systems and third-party services.

• Implement CI/CD pipelines for automated deployment and testing of conversational and agentic AI models and applications.

1. Performance Optimization & Governance (Focused on Conversational & Agentic AI):

• Monitor and optimize the performance of conversational and agentic AI systems, including response latency, accuracy, and user satisfaction.

• Implement robust testing and evaluation frameworks for conversational and agentic AI models, including A/B testing and user feedback analysis.

• Ensure compliance with data privacy and security regulations for conversational and agentic AI applications.

• Implement responsible AI principles into the agentic systems to prevent harmful or unwanted behavior.

1. Collaboration & Stakeholder Engagement:

• Collaborate with product managers, data scientists, and engineers to define and deliver conversational and agentic AI solutions.

• Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner.

• Provide technical guidance and mentorship to junior team members on conversational and agentic AI development.

Qualifications

Who Are We Looking For?

Education

• Education: Bachelor's or Master's degree in Computer Science, AI, Natural Language Processing, or a related field.

Experience

• Experience: 5+ years in IT, with at least 3+ years specializing in Conversational AI and/or Agentic AI solutions.

• Programming Languages: Strong proficiency in Python, with experience in NLP libraries (e.g., Transformers, spaCy, NLTK).

• Cloud Technologies: Deep expertise in Azure and/or AWS with focus on AI services (e.g., Azure Cognitive Services), OpenAI or Bedrock APIs, Azure Machine Learning or AWS Sagemaker, and Azure CoPilot Studio or AWS Lex+Connect with a focus on conversational and agentic AI.

• AI/ML Frameworks: Extensive experience with transformer-based models, LLMs, and dialog management frameworks.

• Database Technologies: Hands-on experience with vector databases (e.g., Azure Cognitive Search, Pinecone, Weaviate), SQL, and NoSQL databases.

• Conversational AI Specific Skills:

• Experience with dialog management systems and frameworks.

• Strong understanding of intent recognition, entity extraction, and sentiment analysis.

• Experience with voice interfaces and speech recognition technologies.

• Agentic AI Specific Skills:

• Experience with agent orchestration frameworks like LangGraph and

• Experience with tool and API integration.

• Understanding of planning and reasoning in AI.

• MLOps & DevOps: Proficiency in CI/CD pipelines, Docker, Kubernetes, and model deployment workflows for conversational and agentic AI.

• Strong communication and collaboration skills.

If this is an opportunity that interests you, we encourage you to apply even if you do not meet 100% of the requirements.

What can you expect from us:

• Opportunities to learn and develop every day through a wide range of programs.
• Internal digital platforms that promote self-learning.
• Development programs according to Leadership skills.
• Specialized training according to the role.
• Learning experiences with internal and external providers.
• We love to celebrate success, which is why we have recognition programs for seniority, behavior, leadership, moments of life, among others.
• Financial wellness programs that will help you reach your goals in all stages of life
• A flexibility program that will allow you to balance your personal and work life, adapting your working day to your lifestyle.
• And because your family is also important to us, they can also enjoy benefits such as our Wellness Line, thousands of Agreements and Discounts, Scholarship programs for your children, Aid Plans for different moments of life, among others.

We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We respect and value diversity as a work force and innovation for the organization.