8 Akrivia Automation Jobs

Job Title: Head of Machine Learning & Agentic Deep Learning Systems

Overview:

We are a global SaaS leader seeking a visionary, hands-on executive to drive our dual-focus AI initiativesadvancing agentic systems alongside deep learning applications by integrating pre-trained large language models (LLMs) through cutting-edge frameworks. This role requires a balance of strategic leadership, technical mastery, and operational excellence to deliver scalable, cloud-native AI solutions that meet the demands of a high-growth SaaS environment.

Key Responsibilities:

• Strategic Leadership & Innovation:
  
• Develop and execute a comprehensive AI roadmap that aligns agentic system strategies with deep learning initiatives tailored for a SaaS platform.
• Drive the integration of pre-trained LLMs (e.g., GPT, BERT) using modern frameworks, ensuring solutions adhere to industry-standard performance benchmarks and safety protocols.
• Collaborate with cross-functional senior leadership to align AI strategies with business objectives, customer needs, and global SaaS trends.
• Define KPIs, OKRs, and performance metrics to track AI initiatives and continuously optimize outcomes.

• Hands-On Technical Expertise:
  
• Architect, develop, and deploy scalable deep learning models and agent-based systems optimized for cloud-native, microservices-based environments.
• Leverage integration frameworks such as LangChain, LangGraph, and LlamaIndex to incorporate LLMs into robust SaaS products, ensuring seamless API integration and system interoperability.
• Implement best practices in MLOps, including CI/CD pipelines, containerization (Docker, Kubernetes), and monitoring to ensure high availability, scalability, and security.
• Evaluate and improve system performance using recognized benchmarks (e.g., GLUE, SuperGLUE, SQuAD) while enforcing rigorous risk assessments and ethical AI standards.

• Team Leadership & Collaboration:
  
• Lead, mentor, and inspire a diverse, cross-functional team of data scientists, ML engineers, and researchers in a fast-paced SaaS environment.
• Foster a culture of continuous innovation and agile methodologies, encouraging collaboration across product, engineering, and business teams.
• Champion knowledge-sharing initiatives and best practices in AI research, development, and deployment, ensuring team alignment with evolving industry standards.

• Operational Excellence & Industry Best Practices:
  
• Establish and enforce best practices for the full AI development lifecycle—from concept through deployment and continuous monitoring.
• Ensure all systems comply with global regulatory standards, data security policies, and ethical guidelines in AI.
• Stay current with emerging trends in AI, cloud computing, and SaaS technologies to ensure our solutions remain cutting-edge and competitive.

Required Qualifications:

• Experience & Background:
  
• 8–12 years of experience in machine learning and deep learning, with a significant focus on agentic frameworks and the integration of pre-trained LLMs in production environments.
• Proven track record in developing, deploying, and scaling AI solutions within a SaaS or cloud-native context.
• Demonstrated ability to balance hands-on technical contributions with effective strategic leadership.

• Technical Skills:
  
• Expertise in agentic architectures, reinforcement learning, and advanced deep learning techniques.
• Proficiency in Python and ML/DL frameworks such as TensorFlow or PyTorch.
• Hands-on experience with integration frameworks like LangChain, LangGraph, and LlamaIndex, as well as cloud platforms (AWS, Azure, GCP).
• Solid understanding of MLOps, CI/CD practices, containerization (Docker, Kubernetes), microservices, and API-driven development.
• Experience with big data tools, distributed computing, and evaluating performance against industry-standard benchmarks.

• Leadership & Communication:
  
• Exceptional leadership skills with experience managing and mentoring high-performing technical teams.
• Strong project management capabilities and a track record of delivering complex, scalable solutions in a SaaS environment.
• Excellent communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:

• Advanced degree (Master’s or Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or a related field.
• Experience contributing to or leading research initiatives in agentic AI and deep learning.
• Familiarity with agile development methodologies, product-led growth strategies, and SaaS business models.
• Proven ability to drive innovation in fast-paced, high-growth global SaaS companies.