Industry Insights

What types of AI roles does your team need? From engineers building machine learning models to managers aligning AI with business strategies, every role adds unique value to your AI initiatives. Here’s a guide to the key roles you should consider when building an AI-powered team.

AI Engineer or Machine Learning Engineer

AI/ML engineers are the backbone of your AI operations. They specialize in designing, developing, and deploying machine learning and AI systems. Their responsibilities include building and optimizing algorithms, training machine learning models, and ensuring seamless integration with existing infrastructure.

Key Skills:

• Proficiency in Python, along with libraries like NumPy, Pandas, and scikit-learn.
• Expertise in machine learning models, including supervised, unsupervised, and reinforcement learning.
• Frameworks like PyTorch or TensorFlow for model training and evaluation.
• Competence in MLOps tools for deploying and maintaining models using Docker, FastAPI, and AWS/GCP.

If you're kickstarting an AI program, hiring a talented AI/ML engineer is essential for creating the systems and pipelines that power your AI initiatives.

AI Research Scientist

AI research scientists push the boundaries of what’s possible with AI. Their focus is on innovation, experimenting with new methods and algorithms to improve existing technologies. If your organization thrives on innovation or contributes to cutting-edge research, this role is indispensable.

Key Skills:

• Strong knowledge of advanced mathematics such as linear algebra, calculus, and statistics.
• Ability to read, analyze, and implement research papers.
• Expertise in frameworks like PyTorch or JAX for creating custom models.
• Contributing to and publishing in open research to establish credibility and drive innovation.

AI research scientists are critical for organizations in industries like healthcare or robotics that require groundbreaking solutions.

Data Scientist

Data scientists turn raw data into actionable insights, making them essential to any AI team. They analyze large datasets to uncover trends, build predictive models, and support data-driven decision-making.

Key Skills:

• Expertise in data wrangling, including working with tools like Pandas and visualizations with Seaborn.
• Profound understanding of statistics and probability for building robust models.
• Use of tools like SQL, Jupyter Notebooks, and MLflow for data processing and model tracking.
• Skills in exploratory data analysis (EDA) and feature engineering.

Data scientists are ideal for businesses looking to leverage data for improved customer experiences, operational efficiencies, or market predictions.

AI Product Manager

An AI product manager bridges the gap between technology and business by aligning AI initiatives with organizational goals. Their role involves defining product success metrics, understanding the capabilities of AI (like large language models or LLMs), and ensuring ethical AI practices.

Key Skills:

• Proficiency in large language models (LLMs) and their practical use cases.
• Ability to connect stakeholder needs with AI technologies to build impactful products.
• Knowledge of prompt libraries and output evaluation for AI applications.
• Focus on ethical considerations and aligning with organizational expectations.

AI product managers guide the AI roadmap, ensuring all efforts are purpose-driven and deliver measurable results.

NLP Engineer

NLP (Natural Language Processing) engineers are responsible for creating language-based AI solutions, such as chatbots, sentiment analysis tools, or summarization systems. With the rise of voice search and conversational AI, these engineers play a significant role.

Key Skills:

• Mastery of tokenization and embeddings, which are key to processing natural language data.
• Application of tools like spaCy, NLTK, and Transformers for building NLP-based systems.
• Fine-tuning LLMs for tasks like question answering, chatbots, or summarization.
• Expertise in RAG pipelines and prompt engineering for enhancing language models.

Adding an NLP engineer to your team can help unlock smarter tools for interacting with your customers.

AI Automation Specialist

Automation is the future, and AI automation specialists leverage AI-powered tools to streamline workflows. Their focus is on creating low-code or no-code automation solutions to improve efficiency at scale.

Key Skills:

• Experience with tools like Make.com, LangChain, and Zapier.
• Knowledge of API/database integration and error handling.
• Familiarity with OpenAI and platforms like CrewAI for task automation.
• Ability to create scalable workflows with minimal code.

An AI automation specialist can reduce repetitive tasks, allowing your team to focus on high-impact initiatives.

Computer Vision Engineer

Computer vision engineers focus on creating AI systems that interpret and process visual data. This expertise is crucial for industries like automotive, healthcare, and retail, where vision-based AI applications are in demand.

Key Skills:

• Proficiency with tools like OpenCV, YOLO, and Detectron2.
• Experience in building convolutional neural networks (CNNs) for image classification.
• Using AI for real-time tasks like OCR, face detection, and gesture identification.
• Competence in managing image datasets like COCO and ImageNet.

Hiring a computer vision engineer ensures your organization can deploy cutting-edge visual AI applications.

AI Agent Developer

AI agent developers focus on autonomous systems that independently complete tasks or behave intelligently. These developers are essential for creating tools like decision-making bots or problem-solving agents.

Key Skills:

• Knowledge of platforms like LangGraph, CrewAI, or AutoGen.
• Building memory modules and protocols, such as ReAct and A2A systems.
• Developing multi-agent systems for collaborative solutions.
• Seamlessly combining tools for real-world use cases.

AI agent developers are key to organizations that want to automate complex processes or build autonomous systems.

Building a Well-Rounded AI Team

Creating a competitive AI team is about finding the right mix of roles like engineers, researchers, product managers, and specialists. Each of these positions brings unique expertise that enables your organization to harness the full potential of AI. Whether you’re aiming to create smarter products or optimize workflows, having the right AI professionals gives your business a critical edge.

Start assembling your AI dream team today. If you’re unsure about where to begin or want to experiment with AI solutions firsthand, reach out to Burtch Works today to explore the possibilities and turn AI into a powerful force for your organization.

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