AI Specialist/Engineer - Qualified Pipeline

Data Meaning; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

A leading consulting firm in Business Intelligence seeks innovative AI Specialists/Engineers to join their remote team. The role involves designing and implementing AI solutions, collaborating with cross-functional teams, and optimizing business processes through AI technologies. Ideal candidates are passionate about AI and possess strong technical skills in machine learning, programming, and data analysis.

Qualifications

• 3+ years of experience with AI/ML frameworks.
• Strong understanding of machine learning algorithms.

Responsibilities

• Design, develop, and implement AI models and algorithms.
• Collaborate with teams to define AI-based solutions.
• Continuously monitor AI systems and improve them.

Skills

Python

Machine Learning

Data Visualization

Problem Solving

Communication

Education

Bachelor’s or Master’s degree in Computer Science

Master’s degree in Artificial Intelligence

Master’s degree in Data Science

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Google Cloud

Azure

Job description

Location: BR/LatAm/USA, Remote
Position type: Full-time Contract (Short Term or Long Term)

Position Summary
Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and beyond. Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management. We have a diverse, global team of consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture.

Job Summary:
We are proactively building a pipeline of innovative and driven AI Specialist/Engineers to join our dynamic team. The ideal candidate will have a passion for artificial intelligence and machine learning, with a strong technical background to design, develop, and implement AI solutions. You will work closely with cross-functional teams to leverage AI technologies to solve complex problems, optimize business processes, and drive strategic decision-making.

Key Responsibilities:

• Design, develop, and implement AI models and algorithms to solve business challenges.
• Apply machine learning techniques (supervised, unsupervised, reinforcement learning) to develop intelligent systems.
• Collaborate with data scientists, software engineers, and business stakeholders to define AI-based solutions.
• Analyze large datasets to extract meaningful insights and develop AI models for predictive analytics.
• Deploy AI models into production environments and ensure their scalability and performance.
• Continuously monitor AI systems and improve them based on performance metrics.
• Research the latest AI trends and emerging technologies to drive innovation.
• Develop and maintain documentation for AI solutions and workflows.
• Provide technical support and guidance to junior team members on AI methodologies.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
• 3+ years of experience working with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Proficient in programming languages such as Python, R, Java, or C++.
• Strong understanding of machine learning algorithms, neural networks, deep learning, and natural language processing (NLP).
• Experience in working with large-scale datasets, data pre-processing, and data visualization tools.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI solutions.
• Ability to work in an agile environment and adapt to changing requirements.
• Excellent problem-solving skills and the ability to think analytically and critically.
• Strong communication skills, with the ability to explain AI concepts to non-technical stakeholders.

Preferred Skills:

• Experience in AI ethics and bias mitigation.
• Knowledge of reinforcement learning and computer vision.
• Experience with AI/ML model monitoring tools like MLflow or Kubeflow.
• Contributions to AI research or publications in AI-related conferences.