Ai serp_jobs.h1.location_city

Job Title : Senior AI / ML Engineer Exp : 10-15 years experienceLocation : North Carolina On-site Role We are seeking a highly experienced AI / ML Engineer with 10-15 years of hands-on engineering and machine learning / AI work, to lead the design, implementation, production deployment and maintenance of advanced AI / ML solutions. You will partner with business, data science, engineering, product and operations teams to drive high-impact AI initiatives, operationalize models in production, define architecture and best practices, mentor evolving teams, and ensure reliability, performance, and scalability of our AI / ML systems. Key Responsibilities : Lead end-to-end AI / ML solution life-cycle : problem definition, data exploration & ingestion, feature engineering, model development, training / tuning, evaluation, deployment, monitoring, and iteration.Architect and build scalable production infrastructure for ML / AI, including model serving, inference pipelines, microservices / API integration, CI / CD for ML (MLOps), monitoring & alerting of model performance.Work with large and complex datasets (structured, semi-structured, unstructured) to derive features and insights, applying advanced ML / AI techniques (deep learning, NLP, CV, generative models, reinforcement learning) as appropriate.Choose appropriate algorithms and frameworks (supervised, unsupervised, deep neural networks, transformer architectures, etc, implement, fine-tune and optimize for latency, throughput, cost, accuracy, and bias / robustness.Deploy solutions into production in cloud and / or on-premises environments; ensure reliability, scalability, high availability, latency constraints, security / compliance.Define and implement MLOps best-practices : versioning, reproducibility, model packaging, automated training pipelines, drift detection, retraining strategies.Serve as technical lead / mentor for AI / ML engineers and data scientists : provide code reviews, design reviews, set engineering and modelling standards, share best practices.Collaborate cross-functionally with product, engineering, architecture, data engineering, operations teams to ensure alignment of AI roadmap with business and technical strategy.Stay current with emerging AI / ML research, tools, frameworks and propose adoption where beneficial; evaluate new platforms, prototype proof-of-concepts, and push innovation.Communicate technical concepts and AI / ML outcomes clearly to non-engineering stakeholders and business leaders; translate metrics and findings into actionable business insight. Required Qualifications : Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics or related quantitative field; Master’s or PhD preferred.10-15 years of experience in software engineering and machine learning / AI engineering roles (building, deploying, operating machine learning models and AI systemsExpertise in programming languages such as Python, and framework experience (e.g., TensorFlow, PyTorch, scikit-learn, KerasProven track record in designing, building, deploying production-grade ML / AI systems in real-world settings.Deep experience in feature engineering, model development, tuning, validation, and model evaluation (metrics, A / B testing, etc.Experience with cloud platforms (AWS, Azure, GCP) or hybrid / edge deployments, including relevant services for data, compute, model serving.Knowledge and experience with model deployment / inference infrastructure, microservices / API integration, containerization (Docker, Kubernetes), distributed computing, streaming or batch pipelines.Strong understanding of MLOps practices : CI / CD for ML, model versioning, monitoring, drift detection, retraining workflows.Solid experience working with large datasets and production data pipelines (ETL / ELT) and experience collaborating with data engineers.Demonstrated ability to mentor / lead engineers, set engineering best practices, and collaborate communication, collaboration and stakeholder-management skills. Preferred Qualifications : Master’s or PhD in a quantitative discipline (Computer Science, AI / ML, Statistics, etc.Experience with advanced AI areas such as large language models (LLMs), generative AI, reinforcement learning, computer vision, NLP at scale.Experience with vector databases, semantic search, embeddings, RAG systems.Prior experience in regulated industries (finance, healthcare, government) with associated compliance, security, audit and explainability requirements.Experience building or leading a team or function (architect-level or principal engineer) within AI / ML.Familiarity with business domain of the company (e.g., manufacturing, fintech, SaaS, logistics etc.Certifications in cloud (AWS Certified ML Specialty, Azure AI Engineer, etc or relevant AI / ML credentials.