Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

Overview

We are looking for an Application Security Engineer with a strong engineering mindset—someone who has built and maintained technical systems and understands how products are developed end‑to‑end. The ideal candidate may come from a security or product background, but must be deeply familiar with the SDLC, CI/CD pipelines, Git workflows, and modern software engineering practices. This role combines hands‑on security engineering with enablement, governance, and cross‑team collaboration.

The Security Engineer will drive application vulnerability management, embed security into development pipelines, and guide engineering teams in building secure-by-design applications. Strong communication skills and the ability to build trusted relationships across both technical and non‑technical stakeholders is essential.

Key Responsibilities

Application Security

• Integrate security best practices into the SDLC and operate, tune, and maintain AppSec tooling (SAST, DAST, SCA).
• Provide secure design guidance, perform secure code reviews, reproduce issues, propose fixes, and validate remediations with developers.

Cloud & Kubernetes Security

• Embed security checks in CI/CD for container images, IaC, and Helm charts & contribute to runtime protections such as admission controls, policy-as-code, scanning, and drift detection.
• Promote secure infrastructure configurations and Kubernetes defaults (RBAC, network policies, PodSecurity, secrets handling, image provenance).

Vulnerability Management & Reporting

• Ensure CI/CD pipelines have robust, effective security coverage and manage exceptions & risk workflows.

• Maintain a consolidated vulnerability backlog with clear ownership and SLA tracking and build automated reporting using tools like Power BI or Excel/Pandas.

Enablement & Governance

• Develop secure coding standards and practical developer guidance.
• Run secure development forums, build and maintain strong relationship with engineering teams and drive application vulnerability management through engagements and reporting.
• Act as a trusted advisor to both engineers and leadership – identifying and communicating risk clearly and persuasively.

Profile Summary: An aspiring and skilled Data Scientist, eager to apply and grow expertise in algorithms and data analysis. Proficient in leveraging Python, Jupyter, and GCP services to analyse and extract insights from complex datasets. Will support key data science initiatives, collaborating with senior data scientists to develop and optimise solutions that drive business value. Focused on contributing to high-impact projects, while building institutional knowledge. 

Key Skills: (Sr Analyst) 

• Upto 3 yrs 

• Strong programming skills in Python and experience using Jupyter notebooks for data analysis and visualisation. 

• Familiarity with GCP services such as BigQuery, Google Cloud Functions and Vertex AI. 

• Solid understanding of machine learning techniques and their application in data activation solutions, including supervised and unsupervised learning, classification, and regression models. 

• Proficiency in data manipulation and cleaning using libraries like Pandas and NumPy, ensuring high-quality datasets for analysis and modelling. 

• Good communication skills, with the ability to articulate findings and support senior team members in presenting insights. 

Description: 

• Assist in the development and implementation of data science algorithms for various strategic initiatives  

• Collaborate with senior data scientists and cross-functional teams to design and execute A/B tests, analysing results to contribute actionable insights and recommendations. 

• Utilise Python and Jupyter notebooks to preprocess and analyse large datasets, identifying trends and patterns that inform strategic decision-making. 

• Contribute to the optimisation of marketing campaigns and other business processes through data-driven approaches. 

• Support the presentation of findings and insights to internal stakeholders, ensuring clarity and impact. 

• Engage in ongoing learning and development to enhance data science capabilities and contribute to team growth. 

Education: 

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline. 

Ideal Certifications: 

• Python for Data Science (Coursera) 

• Google Cloud Machine Learning Engineer (Associate) 

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

#LI-GOC

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

Profile Summary: An aspiring and skilled Data Scientist, eager to apply and grow expertise in algorithms and data analysis. Proficient in leveraging Python, Jupyter, and GCP services to analyse and extract insights from complex datasets. Will support key data science initiatives, collaborating with senior data scientists to develop and optimise solutions that drive business value. Focused on contributing to high-impact projects, while building institutional knowledge.

Key Skills: (Sr Analyst)

• Upto 3 yrs
• Strong programming skills in Python and experience using Jupyter notebooks for data analysis and visualisation.
• Familiarity with GCP services such as BigQuery, Google Cloud Functions and Vertex AI.
• Solid understanding of machine learning techniques and their application in data activation solutions, including supervised and unsupervised learning, classification, and regression models.
• Proficiency in data manipulation and cleaning using libraries like Pandas and NumPy, ensuring high-quality datasets for analysis and modelling.
• Good communication skills, with the ability to articulate findings and support senior team members in presenting insights.

Description:

• Assist in the development and implementation of data science algorithms for various strategic initiatives
• Collaborate with senior data scientists and cross-functional teams to design and execute A/B tests, analysing results to contribute actionable insights and recommendations.
• Utilise Python and Jupyter notebooks to preprocess and analyse large datasets, identifying trends and patterns that inform strategic decision-making.
• Contribute to the optimisation of marketing campaigns and other business processes through data-driven approaches.
• Support the presentation of findings and insights to internal stakeholders, ensuring clarity and impact.
• Engage in ongoing learning and development to enhance data science capabilities and contribute to team growth.

Education:

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.

Ideal Certifications:

• Python for Data Science (Coursera)
• Google Cloud Machine Learning Engineer (Associate)

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

#LI-GOC