Senior AI/ML Specialist

As a Senior AI/ML Specialist at Qvelo, you will take the lead in developing and deploying advanced artificial intelligence (AI) and machine learning (ML) models that solve complex, real-world problems across industries such as healthcare, finance, energy, and government. You will collaborate with cross-functional teams to design cutting-edge AI/ML solutions, optimize them for high-performance environments, and drive innovation in data analytics, predictive modeling, and automation. Your deep expertise in machine learning algorithms, data science, and AI infrastructure will empower organizations to unlock the full potential of their data.

Key Responsibilities:

• Lead the design, development, and implementation of AI and ML models, ensuring they meet performance, accuracy, and scalability requirements for diverse client needs.
• Collaborate with data engineers, data scientists, and business stakeholders to define AI strategies, develop solutions, and deploy models in production environments.
• Optimize AI/ML workflows for high-performance computing (HPC) systems, ensuring that models can scale efficiently across large datasets and complex workloads.
• Implement and fine-tune deep learning algorithms, machine learning frameworks, and natural language processing (NLP) models, ensuring they perform optimally for various use cases.
• Experiment with state-of-the-art AI techniques, staying updated on the latest advancements in machine learning, neural networks, reinforcement learning, and other relevant fields.
• Conduct data preprocessing, feature engineering, and model evaluation to ensure high-quality, reliable results from AI/ML models.
• Develop and deploy AI models using platforms such as TensorFlow, PyTorch, Scikit-learn, Keras, or similar frameworks in high-performance environments.
• Lead model validation and performance tuning efforts, ensuring that AI systems are robust, efficient, and aligned with business goals.
• Mentor junior data scientists and machine learning engineers, providing technical leadership and guidance on best practices in AI/ML development.
• Ensure AI models are production-ready by collaborating with DevOps teams for seamless integration into operational workflows and ensuring ongoing monitoring and maintenance.
• Contribute to the development of custom AI solutions that address specific client challenges, including predictive analytics, recommendation systems, and advanced data mining techniques.
• Communicate complex technical concepts and insights to non-technical stakeholders, translating AI-driven insights into actionable business outcomes.

Requirements:

• Bachelor’s, Master’s, or Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, or a related technical field.
• 5+ years of hands-on experience in AI/ML model development, deployment, and optimization in production environments.
• Expertise in deep learning architectures (CNNs, RNNs, Transformers, GANs) and machine learning algorithms (classification, regression, clustering, etc.).
• Strong proficiency in Python, including experience with AI/ML frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, and other industry-standard tools.
• Experience with big data platforms (Hadoop, Spark) and familiarity with distributed computing techniques for training large-scale models.
• Proven experience in natural language processing (NLP), computer vision, or reinforcement learning.
• Experience in AI model optimization and tuning for high-performance environments, including parallelization and GPU acceleration.
• Familiarity with cloud-based AI/ML services (AWS SageMaker, Google AI, Azure ML) and experience deploying models in cloud and hybrid environments.
• Strong problem-solving skills with a deep understanding of statistics, probability, and data-driven decision-making.
• Excellent communication skills, with the ability to explain complex AI/ML concepts to both technical and non-technical audiences.
• Experience with model interpretability and explainability tools, ensuring transparency and accountability in AI-driven decisions.

Preferred Qualifications:

• Experience with AI/ML for high-performance computing (HPC) environments, optimizing models for large-scale simulations and data-intensive workloads.
• Proficiency in SQL, NoSQL databases, and working with large datasets.
  Knowledge of AI ethics, fairness, and bias mitigation in machine learning models.
• Experience with DevOps practices for AI/ML, including model versioning, continuous integration, and deployment pipelines (MLOps).
• Familiarity with quantum machine learning or emerging AI techniques that leverage quantum computing.