AI/ML Solution Architect

Job Title: AI/ML Solution Architect

Location: Remote

About the Role:

We are seeking a highly skilled and experienced AI/ML Solution Architect to lead the design and implementation of AI and machine learning solutions across our organization. You will play a key role in shaping the AI/ML strategy, guiding the technical development of innovative solutions, and ensuring the scalability and sustainability of machine learning systems.

Key Responsibilities:

• Architecture & Design: Design end-to-end AI/ML solution architectures that align with business objectives and technical requirements.
• Solution Development: Lead the prototyping and development of scalable AI/ML models and platforms.
• Technology Integration: Integrate AI/ML models into existing enterprise platforms, ensuring seamless operation and performance.
• Stakeholder Collaboration: Work closely with data scientists, software engineers, product managers, and business stakeholders to gather requirements and deliver impactful solutions.
• Governance & Best Practices: Establish and enforce best practices for model development, MLOps, model explainability, and responsible AI.
• Evaluation & Validation: Lead model performance evaluation, A/B testing, and deployment readiness checks.
• Innovation & Research: Stay abreast of industry trends, tools, and technologies in AI/ML to drive innovation within the organization.

Qualifications:

• Bachelor's or Master s degree in Computer Science, Data Science, Engineering, or related field. Ph.D. is a plus.
• 7+ years of experience in software engineering or data science, with 3+ years in a solution architecture or technical leadership role.
• Deep expertise in machine learning, deep learning, and statistical modeling techniques.
• Strong programming skills in Python, Java, or Scala, with experience using ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.
• Proficient in cloud platforms (AWS, Azure, Google Cloud Platform) and tools like SageMaker, Databricks, or Vertex AI.
• Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Strong communication and leadership skills; ability to translate complex technical concepts into business terms.

Preferred Qualifications:

• Experience in industry-specific AI/ML use cases (e.g., finance, healthcare, retail, manufacturing).
• Knowledge of data privacy, ethics, and compliance issues in AI.
• Familiarity with large language models (LLMs), generative AI, and advanced NLP techniques.