TITLE: Machine Learning Engineer Intern – Voice AI

POSITION OVERVIEW:

The Machine Learning Engineer Intern will contribute to the development of ALEBEX's production Voice AI systems, working across machine learning model training, post-training, evaluation, and real-time inference. This role offers hands-on experience with speech models, large language models, GPU-based inference, low-latency systems, and real-time voice pipelines.

Working closely with the engineering team, the successful candidate will help fine-tune, evaluate, optimize, and deploy machine learning models used in production voice agents. This is a hands-on engineering role involving real models, GPUs, production inference workloads, and real-time systems.

This position is ideal for a student or recent graduate with strong Python and machine learning fundamentals who is interested in applied AI and wants practical experience taking models from training and experimentation into production environments.

EMPLOYMENT TYPE: Co-op / Internship 4- or 8-Month Contract

COMPENSATION: $30 per hour

LOCATION: Downtown Vancouver, BC (Alexander Innovation Centre)

WORK WEEK: Monday – Friday; Full time preferred.

ABOUT ALEXANDER INNOVATION CENTRE (AIC):

Alexander Innovation Centre is a Vancouver-based innovation hub supporting the development and commercialization of emerging technologies and fostering collaboration between industry, education, and entrepreneurs. Located in downtown Vancouver, the Centre provides a collaborative environment for technology development, applied innovation, and hands-on learning opportunities.

This position is based at the Alexander Innovation Centre, where the successful candidate will work closely with the ALEBEX AI team on the development of production AI technologies.

ABOUT ALEBEX:

ALEBEX AI is a Canadian-owned AI company based in Vancouver, BC, focused on developing an agentic workforce platform where AI agents perform real operational work — including answering calls, qualifying leads, and executing multi-step tasks — under human supervision.

The platform enables AI agents to operate across voice and digital channels, combining real-time communication, proprietary voice technology, AI models, integrations, and orchestration to execute real business workflows. It operates on Canadian infrastructure, including on-premises AI inference, and is currently used in production by real clients.

ALEBEX is a small, fast-moving team focused on developing practical AI solutions for real-world business applications. Its technology is built for production use, with active customers and operational workflows rather than demonstrations or experimental prototypes.





The successful candidate will work with the ALEBEX AI team on the development, evaluation, and optimization of machine learning models powering its Voice AI platform as part of this internship.

QUALIFICATIONS:

- Currently enrolled in a co-op-eligible program in Computer Science, Machine Learning, Artificial Intelligence, Electrical Engineering, or a related STEM field.
- Strong Python programming skills.
- Familiarity with PyTorch and modern deep learning workflows.
- Hands-on experience with at least some of the following:

o Supervised Fine-Tuning (SFT) o LoRA, QLoRA, PEFT, or related post-training techniques o Hugging Face Transformers o LLM or speech model fine-tuning o GPU-based model inference o Online or real-time model serving
- Positive understanding of transformer architectures and modern LLMs.
- Comfortable working in a Linux environment.
- Strong problem-solving skills and willingness to learn.

PREFERRED QUALIFICATIONS:

- Experience with Voice AI, ASR, TTS, VAD, turn detection, or speech-language models.
- Experience deploying models with vLLM, TensorRT-LLM, Triton, ONNX Runtime, or similar inference frameworks.
- Understanding of KV caching, batching, quantization, prefix caching, or speculative decoding.
- Experience with Docker and cloud GPU environments such as AWS.
- Experience evaluating latency-sensitive machine learning systems.

SPECIFIC RESPONSIBILITIES: Model Training & Post-Training

- Fine-tune LLMs and speech models using SFT, LoRA, QLoRA, PEFT, and related post-training techniques.
- Experiment with training strategies, model configurations, and datasets.
- Support the development and improvement of models for Voice AI applications.

Voice AI & Speech Models

- Build and improve models for ASR, turn detection, interruption handling, intent understanding, and other Voice AI tasks.
- Work with speech, language, and speech-language models used within real-time voice agents.
- Help evaluate model behaviour across different voice and conversational scenarios.

Data & Evaluation

- Prepare, clean, organize, and validate datasets used for model training and evaluation.
- Build and maintain evaluation pipelines for machine learning models.
- Benchmark models across accuracy, latency, resource usage, and other relevant metrics.

Real-Time Inference & Optimization





- Deploy machine learning models for online and real-time inference.
- Optimize inference latency, throughput, GPU memory usage, and concurrency.
- Experiment with batching, caching, quantization, and other inference optimization techniques.

ML Infrastructure & Integration

- Work with inference frameworks such as vLLM, Hugging Face Transformers, PyTorch, ONNX Runtime, or similar technologies.
- Help integrate machine learning models into ALEBEX's real-time Voice AI infrastructure.
- Support model serving, deployment, monitoring, and performance testing.

Experimentation & Engineering

- Experiment with model architectures, training approaches, and inference optimizations.
- Investigate technical problems and contribute practical solutions.
- Document experiments, findings, benchmarks, and implementation decisions.

Production Voice AI Systems

- Help develop machine learning systems that operate under real-world production constraints.
- Evaluate trade-offs between model accuracy, latency, reliability, GPU resource usage, and cost.
- Monitor and troubleshoot model behaviour in production inference environments.

WHY JOIN THE TEAM:

- Groundbreaking Projects – Work on AI, robotics, and industry-disrupting software.
- Innovation Culture – Be part of a team that values experimentation, creativity, and rapid delivery.
- Career Growth – Opportunities to lead projects and shape the future of our AI-augmented development strategy.
- Central Location – Based in downtown Vancouver at Alexander Innovation Centre (570 Dunsmuir Street).
- Facilities – Brand new campus and office space that emphasizes a culture of environmentally friendly practices. Secure bike lockers and shower.

HOW TO APPLY: Email your application to [email protected], using the subject line:

"[Your Full Name]_Machine Learning Engineer Intern (Voice AI)"

Please include

- Resume/CV or LinkedIn profile.
- A link to something you have built, such as GitHub, a live project, or a short screen recording. We would rather see one meaningful project than a long list of projects.

Only shortlisted applicants will be contacted. No phone calls please. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. Thank you.

Pay: Up to $30.00 per hour

Benefits

- Company events
- Dental care
- Employee assistance program
- Extended health care
- On-site gym
- Paid time off
- Vision care

Ability to commute/relocate:
- Vancouver, BC: reliably commute or plan to relocate before starting work (required)

Language:
- English (required)

Work Location: In person

📌 Machine Learning Engineer Intern – Voice AI (Vancouver)
🏢 Alexander Innovation Centre
📍 Vancouver