Genai Ml Engineer Job at Randstad (Toronto)

AI / ML Engineer

AI / ML Engineer – Outside IR35 – Hybrid (2–3 days in Marble Arch) – 6 Months. O...

Location

United Kingdom , London

Salary:

Not provided

Orbis Consultants

Expiration Date

Until further notice

Requirements

Strong Python skills and real-world ML engineering experience
Strong experience with modern GenAI / LLM frameworks: LangChain, LangGraph, PyTorch, etc.
Comfort working with unstructured data: entity extraction, semantic search, vectorisation, RAG-like patterns
Awareness of data engineering: pipelines, legacy data extraction, interfacing with data teams
Experience or strong curiosity working with Azure and Azure Databricks
A proactive stakeholder mindset – you enjoy teasing out real needs rather than waiting for specs
A learner’s mindset – you keep up with the pace of AI and explore new tooling constantly

Job Responsibility

Act as a hands-on AI / ML engineer embedded directly in the business problem space
Take ambiguous business challenges and refine them into real, provable AI use-cases
Prototype solutions quickly, demo them internally, gather feedback and iterate
Work with huge volumes of unstructured documents and data across multiple legacy systems
Use GenAI, LLMs and semantic modelling to extract meaning, entities and patterns
Build end-to-end solutions — from extraction to model testing to productionisation
Collaborate with business stakeholders, data engineers and external vendors / startups
Help influence and define the AI roadmap and tooling choices going forward

Research Engineer, GenAI

You will be part of Kiddom’s Data Science team, building the foundation of our s...

Location

United States , San Francisco; New York

Salary:

175000.00 - 250000.00 USD / Year

Kiddom

Expiration Date

Until further notice

Requirements

5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets
1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python
Fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

What we offer

Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State
Commuter and FSA plans

Fulltime

GenAI Engineer

We are seeking a talented and experienced Generative AI Engineer to lead the dev...

Location

Portugal , Lisbon

Salary:

Not provided

Inetum

Expiration Date

Until further notice

Requirements

Proven experience in Machine Learning, Generative AI, or related fields
Strong leadership and communication skills
Advanced knowledge of integrating Generative AI into cloud infrastructures
Ability to design and implement AI strategies at scale
Proficiency in Python and relevant ML libraries
Experience with LangChain, Semantic Kernel, Hugging Face Transformers
Familiarity with Apache Lucene/Solr/LuceneSearch
Experience building applications with LLMs on Microsoft Azure (GPT-4o, o3)
Use of Azure OpenAI models (GPT-3.5 Turbo, GPT-4)
Experience with Azure AI Services (genai-ltst, gpt-4o-mini-realtime-preview)

Job Responsibility

Independently develop GenAI-based applications tailored to product requirements
Implement scalable and high-performance AI solutions
Integrate AI applications with existing internal systems
Lead and collaborate with cross-functional teams to drive AI strategy and execution

What we offer

Inetum certified Top Employer Europe 2025
Opportunity to grow your expertise
Create digital impact quickly, easily and for the good of all

Fulltime

Avp ml and genai model validation

Embark on a transformative journey as an AVP ML and GenAI Model Validation at Ba...

Location

India , Noida

Salary:

Not provided

Barclays

Expiration Date

Until further notice

Requirements

Highly numerate, evidenced by an Honours degree, master’s, or PhD (or equivalent) in a quantitative discipline such as Computer Science, Mathematics, Physics, Operational Research, Economics, Engineering, or Finance
Experience developing, validating, or independently reviewing best‑in‑class tools and AI/ML models for large financial institutions or comparable regulated environments, with the ability to effectively challenge and improve model methodologies and model management processes
Strong analytical and technical expertise in AI/ML modelling, including experience with ML algorithms (e.g., XGBoost, LightGBM, Random Forest), NLP models, and deep learning frameworks (e.g., TensorFlow, PyTorch, Keras)
Experience developing or validating AI/ML models on large datasets in Hadoop/AWS environments
Designed, fine‑tuned, and shipped Generative AI models - transformer‑based LLMs, RAG systems for grounded retrieval, and GANs-using PyTorch/TensorFlow and Hugging Face, including prompt engineering, RLHF, and rigorous evaluation of GenAI models
Hands‑on experience with Generative AI technologies, including Large Language Models, Transformers, retrieval‑augmented generation (RAG), and prompt‑based systems
familiarity with LangChain and LangGraph
Experience designing, developing, validating, or reviewing agent‑based AI architectures, including multi‑agent orchestration, task planning, memory management, and safeguard mechanisms
Sound understanding of financial services regulatory expectations and model risk guidance (e.g., SR 11‑7, SS1/23, IFRS 9, EU AI Act etc.)
Strong communication and influencing skills, with the ability to produce high‑quality written material for both technical and senior non‑technical audiences

Job Responsibility

Validation of models for their intended use and scope, commensurate with the complexity and materiality of the models
Approval or rejection of a model or usage based on assessment of the model’s conceptual soundness, performance under intended use and the clarity of the documentation of the model’s inherent risks, limitations and weaknesses
Assessment of any compensating controls used to mitigate Model risk
Documentation of validation findings and recommendations in clear and concise reports, providing actionable insights for model improvement
Evaluation of the coherence of model interactions and quality of Large Model Framework aggregate results that generate output for regulatory submissions or management decision making and planning
Design of the framework and methodology to measure and, where possible, quantify model risk, including the assessment of framework level uncertainty

What we offer

Hybrid working
Modern workspaces, collaborative areas, and state-of-the-art meeting rooms
Facilities include wellness rooms, on-site cafeterias, fitness centers, and tech-equipped workstations

Fulltime

ML Tech Lead, GenAI

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...

Location

Salary:

Not provided

Provectus

Expiration Date

Until further notice

Requirements

Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models)
Strong expertise in AWS Cloud Services
Strong experience in ML/AI, including at least 2 years in a leadership role
Hands-on experience with Python, TensorFlow/PyTorch, and model optimization
Familiarity with MLOps tools and best practices
Excellent problem-solving and decision-making abilities
Strong communication skills and the ability to lead cross-functional teams
Passion for mentoring and developing engineers

Job Responsibility

Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment
Drive the roadmap for machine learning projects aligned with business goals
Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery
Design, develop, and fine-tune LLMs and other machine learning models to solve business problems
Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction
Stay ahead of advancements in LLMs and apply emerging technologies
Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML
Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.)
Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS
Ensure best practices in security, monitoring, and compliance within the cloud infrastructure

ML Practice Leader (GenAI)

A Practice Leader is the first point of contact for their direct reports, and th...

Location

Salary:

Not provided

Provectus

Expiration Date

Until further notice

Requirements

Practical experience and strong understanding of Python patterns & best practices
Strong understanding of ML project lifecycle
Practical experience with creating training datasets involving human annotators
Experience with writing Deep Learning models from scratch
Experience in >1 of the following areas: NLP, CV, forecasting, recommender systems
Strong experience with agentic workflows, RAG architecture, and GraphRAG
Experience and in-depth understanding of transformers
Practical experience with /AWS/other cloud/open source alternatives/ MLOps platforms, frameworks, and libraries
Practical experience with model post-production & maintenance: model and data monitoring, retraining automation, etc.
Ability to make reusable components of ML pipelines

Job Responsibility

Build effective teams
Participate in meetups, conferences, and build community
Share best practices and culture with the team
Mentor engineers, coach Team Leads, and encourage others to share knowledge
Have technical excellence and be an influencer in different teams/projects
Hire and onboard newcomers
Conduct performance reviews, 1-on-1 meetings
Identify and address team gaps in knowledge
Evaluate, improve, and maintain processes
Сollaborate with other managers across the company

AI Solutions Engineer

AI Solutions Engineer for Arize AI, the leading AI & Agent Engineering observabi...

Location

United States

Salary:

125000.00 - 175000.00 USD / Year

Arize

Expiration Date

Until further notice

Requirements

Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production
Comfortable working in public Cloud environments (AWS, Azure, GCP)
Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
Understanding of GenAI concepts and application evaluation + development lifecycle
Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
Strong Communication Skills - Ability to simplify complex, technical concepts
A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV

Job Responsibility

Work closely with some of the most sophisticated ML / GenAI teams in the world
Act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders
Advise on GenAI and ML best practices
Give ML and LLM product demos to technical and business stakeholders
Run strategic business reviews for customers in partnership with our sales team
Interface with our pre-sales engineering team to gather client goals and KPI’s
Partner with our product and engineering teams to help drive the product roadmap
Spearhead new opportunities within existing accounts to help drive expansions

What we offer

competitive equity package
comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support
WFH monthly stipend to pay for co-working spaces

Fulltime

AI Solutions Engineer

AI Solutions Engineer for Arize AI, the leading AI & Agent Engineering observabi...

Location

United States , Raleigh

Salary:

125000.00 - 175000.00 USD / Year

Arize

Expiration Date

Until further notice

Requirements

Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production
Comfortable working in public Cloud environments (AWS, Azure, GCP)
Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
Understanding of GenAI concepts and application evaluation + development lifecycle
Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
Strong Communication Skills - Ability to simplify complex, technical concepts
A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV

Job Responsibility

Work closely with some of the most sophisticated ML / GenAI teams in the world
Act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders
Advise on GenAI and ML best practices
Give ML and LLM product demos to technical and business stakeholders
Run strategic business reviews for customers in partnership with our sales team
Interface with our pre-sales engineering team to gather client goals and KPI’s
Partner with our product and engineering teams to help drive the product roadmap
Spearhead new opportunities within existing accounts to help drive expansions

What we offer

competitive equity package
comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support
WFH monthly stipend to pay for co-working spaces

Fulltime

Genai Ml Engineer

Randstad

Location:
Canada , Toronto

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 13, 2026

Expiration:
March 09, 2026

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Job Posted:
January 13, 2026

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