Lead AI/ML Ops Engineer

HCLTech; Greater London; On-site; USD 60,000 - 100,000; Full time

Job summary

An established industry player is looking for a Lead AI/ML Ops Engineer to spearhead the operational stability and performance of advanced recommendation systems. This pivotal role involves overseeing the NBO models, ensuring data quality, and guiding the development of cutting-edge ML techniques. You will collaborate with various stakeholders, mentor engineers, and drive the documentation efforts for NBO processes. If you have a passion for machine learning and a knack for problem-solving, this opportunity offers a chance to make a significant impact in a dynamic and innovative environment.

Qualifications

• 10+ years of experience in Data Science and ML, particularly in personalization.
• Strong programming skills in Python and experience with ML frameworks.

Responsibilities

• Oversee operations and troubleshooting of NBO models on GCP.
• Lead design and implementation of enhancements for NBO suite.

Skills

Data Science

Machine Learning

Python

R

ML frameworks (scikit-learn, PyTorch)

Recommendation Systems

SQL

GCP (Google Cloud Platform)

CI/CD processes

Problem-solving

Tools

GCP BigQuery

GitHub Actions

Job description

HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered on digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of $13+ billion.

Job Description 2: Lead AI/ML Ops Engineer (Recommendation Systems Focus)

• Role: Lead AI/ML Ops Engineer
• Experience Level: Senior
• Core Objective: Take a leading role in maintaining the operational stability, performance, and ongoing development of the Next Best Offer (NBO) models. Oversee necessary enhancements, ensure smooth execution across various NBO modules (Alert, Core, Eval, Scoring, Retention), and facilitate effective knowledge transfer.

Key Responsibilities:

• Oversee the day-to-day operations, monitoring, and troubleshooting of the NBO models running on GCP and potentially on-premise servers.
• Lead the design, implementation, and validation of new business requirements and enhancements for the NBO suite.
• Ensure continuous monitoring, supervision, and version upgrades of the diverse NBO models.
• Guide the further development of ML models within NBO, potentially incorporating advanced techniques like GNNs, autoencoders, or transformers.
• Oversee data validation processes and ensure data quality for NBO inputs.
• Manage the NBO model evaluation framework (NBO Eval) and report on performance metrics (accuracy, coverage, personalization).
• Coordinate with relevant departments regarding architecture maintenance and regulatory aspects if applicable to NBO.
• Collaborate closely with stakeholders to communicate model performance, development progress, and quarterly benefits where applicable.
• Mentor mid-level engineers within the vendor team, particularly on NBO specifics.
• Actively participate in and help coordinate the intensive knowledge handover from departing employees within the first 1.5-2 months.
• Lead the documentation efforts for NBO processes, models, and enhancements.
• Support the final handover process to the new internal team towards the end of the engagement.

Required Skills & Experience:

• 10+ years of hands-on experience in Data Science and Machine Learning, applying models in a business context, particularly for personalization or recommendation.
• Proven experience leading the development, deployment, and lifecycle management of complex ML systems.
• Strong programming skills in Python and potentially R.
• Expertise with relevant ML frameworks (e.g., scikit-learn, PyTorch).
• Experience with recommendation systems, collaborative filtering, and ideally Graph Neural Networks (GNNs).
• Proficient with SQL and working with large datasets (e.g., GCP BigQuery).
• Experience with cloud platforms (specifically GCP) and CI/CD processes (specifically GitHub Actions).
• Experience deploying models in containerized applications.
• Excellent problem-solving skills and ability to quickly adapt to new model types and requirements.
• Strong communication and stakeholder management skills.
• Expertise in advanced neural network architectures (Autoencoders, Transformers).
• Ability to rapidly acquire complex domain knowledge.

Seniority Level

• Mid-Senior level

Employment Type

• Full-time

Job Function

• Other
• Industries: Banking and Financial Services