Machine Learning Engineer - 2

Job Description

TELUS Digital (TD) Experience partners with the worlds most innovative brands, from tech startups to industry leaders in fintech, gaming, healthcare, and more. We empower businesses to scale and redefine possibilities with integrated customer experience and cutting-edge digital solutions.

Backed by TELUS, our multi-billion-dollar parent company, we offer scalable, multi-language, and multi-shore capabilities. Our expertise spans digital transformation, AI-driven consulting, IT lifecycle management, and more delivered with secure infrastructure, value-driven pricing, and exceptional service.

AI Data Solutions: Shaping the Future of AI

For nearly two decades, Telus Digital AI Data Solutions has been a global leader in providing premium data services for the ever-evolving AI ecosystem. From machine learning to computer

vision and Generative AI (GenAI), we empower the next generation of AI-powered experiences with high-quality data and human intelligence to test, train and improve AI models.

Backed by a community of over one million contributors and proprietary AI-driven tools, we deliver solutions designed to cover the training data needs of every project. From custom data

collection to advanced data annotation and fine-tuning, our purpose-built tools deliver multimodal data for AI training projects of any complexity from experimental pilots to ambitious large-scale programs. Examples include empowering GenAI models with human-aligned datasets and fine-tuning data across 20+ domains and 100+ languages, enabling autonomous driving and advancing extended reality applications with industry-leading data labelling.

Join us to be part of an innovative team shaping the future of AI and driving digital

transformation to new heights!

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Machine Learning Engineer Level 2 (NLP)

Role Overview

As an MLE-2 in NLP, you will independently own ML modules for applications such as search, summarization, dialogue systems, and text classification. Youll fine-tune LLMs, build evaluation pipelines, and contribute to applied research exploration.

Technical Expectations

Programming & Frameworks

Strong proficiency in Python

Experience managing model training pipelines

Builds reusable components (tokenization, caching, distributed training)

NLP Expertise

Fine-tuning BERT, GPT, T5, LLaMA for custom tasks

Strong understanding of seq2seq, attention, masking, prompt engineering

Hands-on with NER, QA, summarization, retrieval-augmented generation

Evaluation & Experimentation

Familiarity with BLEU, ROUGE, perplexity, diversity scores

Designed and executed A/B tests, qualitative user studies, blind evaluations

Built interpretable error analysis dashboards

Deployment & Ops

Deployed NLP APIs (FastAPI, Flask, TorchServe)

Knowledge of ONNX, quantization, LoRA (low-rank adaptation)

Set up experiment tracking & hyper-parameter optimization

Soft Skills Expectations

Owns roadmap for a submodule (e.g., summarization engine, feedback scorer)

Actively mentors MLE-1s / interns

Collaborates with data, product, and infra teams to scope, deliver & ensure adoption of ML features