Artificial Intelligence Engineer

Job Summary

We are looking for a highly skilled Artificial Intelligence (AI) Engineer to design, develop, and deploy AI-driven solutions that enhance our clients' digital transformation initiatives at Data2Bots. You will be responsible for building machine learning models, developing AI algorithms, and integrating AI capabilities into diverse client systems across multiple industries. This role is ideal for someone who enjoys problem-solving, has strong software engineering fundamentals, and is passionate about turning complex data into real-world business applications that drive measurable client outcomes.

Key Responsibilities

• Design, develop, and implement AI models, machine learning algorithms, and deep learning solutions tailored to specific client requirements and business objectives.
• Train and fine-tune machine learning models using large, complex datasets to improve accuracy and performance and deliver actionable business insights.
• Build and optimize AI-driven applications, including natural language processing (NLP), computer vision, recommendation systems, predictive analytics, and intelligent automation solutions.
• Develop and integrate AI models into cloud-based and edge computing environments, ensuring seamless deployment across client infrastructures.
• Work with structured and unstructured data from diverse sources, applying advanced data preprocessing, feature engineering, and data augmentation techniques.
• Collaborate with cross-functional teams, including data scientists, software engineers, DevOps specialists, and business analysts, to align AI solutions with client business objectives and technical requirements.
• Deploy AI models to production environments, monitor their performance in real-world scenarios, and continuously improve them based on client feedback and evolving business needs.
• Research and stay up to date with the latest AI advancements, frameworks, and industry best practices to enhance Data2Bots' AI capabilities and competitive advantage.
• Optimize AI models for efficiency, scalability, cost-effectiveness, and real-time processing to meet demanding client performance requirements.
• Ensure AI models adhere to ethical AI principles, fairness standards, bias mitigation techniques, and responsible AI deployment practices across all client engagements.
• Participate in client meetings, technical presentations, and solution demonstrations to communicate AI capabilities and project outcomes effectively.

Required Skills & Qualifications

• Bachelor's or master's degree in computer science, artificial intelligence, machine learning, data science, or a related technical field.
• Minimum 3-5 years of proven experience in AI/ML model development, training, and production deployment in business environments.
• Expert-level proficiency in Python with extensive experience in AI/ML development; knowledge of R, Java, or Scala is advantageous.
• Hands-on experience with machine learning frameworks, including TensorFlow, PyTorch, Scikit-learn, Keras, and Hugging Face Transformers.
• Strong understanding of deep learning architectures, NLP techniques, computer vision applications, reinforcement learning, and generative AI models (GPT, BERT, CNNs, RNNs, Transformers).
• Extensive experience working with cloud platforms (AWS SageMaker, Azure ML Studio, GCP AI Platform) for AI model deployment and management.
• Knowledge of big data technologies such as Apache Spark, Hadoop, Kafka, or distributed computing frameworks for handling large-scale datasets.
• Experience with MLOps tools and practices, including MLflow, Kubeflow, Docker, Kubernetes, and CI/CD pipelines for model monitoring, retraining, and continuous deployment.
• Strong analytical and problem-solving skills with demonstrated ability to translate business requirements into technical AI solutions.
• Excellent communication and teamwork skills, with proven ability to explain complex AI concepts to both technical and non-technical stakeholders in client-facing environments.
• Experience working in consulting or client services environments with the ability to manage multiple projects simultaneously.
• Demonstrated track record of delivering AI projects from conception to production deployment.

Preferred Qualifications

• Experience in deploying AI models in real-world applications such as intelligent chatbots, fraud detection systems, predictive analytics platforms, document processing automation, recommendation engines, and computer vision solutions.
• Knowledge of edge AI deployment, IoT applications, and mobile AI optimization techniques.
• Contributions to AI research publications, open-source AI projects, or technical community initiatives.
• Experience with modern data engineering tools and practices, including data lakes, data warehouses, and streaming data processing.
• Knowledge of API development, microservices architecture, and system integration for AI applications.
• Familiarity with agile development methodologies and project management tools used in consulting environments.
• Certifications in cloud AI services (AWS Certified Machine Learning, Azure AI Engineer, Google Cloud Professional ML Engineer) or relevant AI/ML specializations.