Senior Data Engineer (Hybrid role)

at  PDF Solutions

Overview:
PDF was recognized by Forbes as one of America’s Best Small Employers for 2023. This ranking highlights only 300 companies out of 10,000+ that were considered in the Forbes nationwide analysis and PDF solutions ranked 55! The results are based on an employee satisfaction survey as well as a social listening analysis of employee feedback conducted by a Forbes research firm.
If you possess deep expertise in both AI/ML and large-scale data engineering, and you find excitement in architecting transformative analytics solutions, then this is your call. We’re seeking a seasoned professional to lead our AI/ML initiatives within the context of big data, pushing the boundaries of predictive analytics and data-driven insights.

Responsibilities:

• Architect Large-Scale AI/ML Solutions: Design scalable, robust AI/ML pipelines, integrating distributed computing frameworks (Spark, etc.) for efficient big data processing and model training.
• Champion Model Optimization & Deployment: Drive performance tuning, model selection, and create seamless deployment strategies for production environments, ensuring real-time insights.
• Oversee Data Infrastructure: Collaborate with data engineers to architect big data systems that support AI/ML workloads, ensure data quality, and guide optimization for model requirements.
• Lead Research & Innovation: Initiate and oversee research into promising new AI/ML techniques or libraries specifically relevant to large-scale data challenges.
• Mentor & Guide: Provide technical leadership, mentor junior colleagues, and establish best practices across the analytics team.

Qualifications:

• Advanced Degree & Experience: MS/Ph.D. in Computer Science, Data Science, or a related field. 10+ years of proven experience designing and implementing AI/ML solutions within big data environments.
• Big Data Mastery: Expertise in Spark, Hadoop Ecosystem, cloud-based big data technologies, and distributed computing principles.
• Deep AI/ML Fluency: Extensive knowledge of supervised/unsupervised learning, deep learning frameworks (TensorFlow, PyTorch, etc.), NLP, or other specialized AI/ML domains.
• Strategic Thinker: Ability to translate business objectives into AI/ML project roadmaps, identify potential ROI, and evaluate technologies strategically.
• Exceptional Communication & Leadership: Proven ability to communicate complex technical concepts to a variety of stakeholders, inspire collaboration, and lead teams towards a unified vision.

• Architect Large-Scale AI/ML Solutions: Design scalable, robust AI/ML pipelines, integrating distributed computing frameworks (Spark, etc.) for efficient big data processing and model training.
• Champion Model Optimization & Deployment: Drive performance tuning, model selection, and create seamless deployment strategies for production environments, ensuring real-time insights.
• Oversee Data Infrastructure: Collaborate with data engineers to architect big data systems that support AI/ML workloads, ensure data quality, and guide optimization for model requirements.
• Lead Research & Innovation: Initiate and oversee research into promising new AI/ML techniques or libraries specifically relevant to large-scale data challenges.
• Mentor & Guide: Provide technical leadership, mentor junior colleagues, and establish best practices across the analytics team