AI Specialist/Engineer - Qualified Pipeline

Data Meaning; Brasil; Teletrabalho; BRL 120.000 - 160.000; Tempo integral

Resumo da oferta

A leading data consulting firm is seeking an AI Specialist/Engineer to design and implement innovative AI solutions. This remote role requires a degree in Computer Science and experience with AI/ML frameworks. Ideal candidates have strong analytical skills and can communicate AI concepts to stakeholders effectively.

Qualificações

• 3+ years of experience with AI/ML frameworks.
• Strong understanding of machine learning algorithms and NLP.
• Experience in large-scale datasets and data visualization.

Responsabilidades

• Design and implement AI models and algorithms.
• Collaborate with data scientists and engineers.
• Analyze datasets for insights and predictive analytics.

Conhecimentos

AI/ML frameworks experience

Programming (Python, R, Java, C++)

Strong analytical skills

Communication skills

Formação académica

Bachelor’s or Master’s degree in Computer Science or related field

Ferramentas

TensorFlow

PyTorch

AWS

Google Cloud

Scikit-learn

Descrição da oferta de emprego

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.