Senior Applied Machine Learning Engineer - Asset Intelligence Job at MaintainX (San Francisco)

New

Senior Applied Machine Learning Engineer - Asset Intelligence

We are seeking a highly skilled and motivated Senior Applied Machine Learning En...

Location

Canada , Montreal, Toronto, Vancouver

Salary:

Not provided

MaintainX

Expiration Date

Until further notice

Requirements

7+ years of experience in Machine Learning, Data Science, or Applied AI
Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar)
Proven experience deploying production ML systems at scale
Strong background in LLMs, time-series modeling, and anomaly detection for real-world data
Demonstrated ability to lead architectural decisions, mentor engineers, and collaborate across product, data, and platform teams
Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker)
Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred

Job Responsibility

Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products
Architect end-to-end ML systems—from data ingestion and feature engineering to model training, deployment, and monitoring
Mentor a growing team of ML and data engineers, instilling best practices for experimentation, evaluation, and model lifecycle management
Partner with product and engineering leaders to align AI roadmap with customer needs and business goals
Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining
Drive performance optimization through techniques like quantization, distillation, and scalable inference serving
Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence
Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security

What we offer

Competitive salary and meaningful equity opportunities
Healthcare, dental, and vision coverage
401(k) / RRSP enrollment program
Take what you need PTO

Senior Artificial Intelligence/Machine Learning Modeller- Global Markets

This is an exciting opportunity to join the Barclays team in Singapore as a seas...

Location

Singapore , Singapore

Salary:

Not provided

Barclays

Expiration Date

Until further notice

Requirements

Master’s degree in a Science, Technology, Engineering and Mathematics (STEM) field (PhD preferred)
A proven record of a strong foundation in Machine Learning, data science, and software engineering
Proven experience with Python
Deep expertise in one of the following: Natural Language Processing (NLP), Reinforcement Learning, Time Series, Algorithmic Trading and Machine Learning Engineering
Demonstrated success and passion for crafting solutions that are both technically rigorous and operationally effective
Champions a collaborative mindset and a drive to learn, iterate, and improve
Responsible for mentoring team members, linking up with key stakeholders, managing projects, and spearheading R&D thinking

Job Responsibility

Development and implementation of quantitative models and strategies to derive insight into market trends and optimize trading decisions, pricing, and risk management across various financial products and markets
Working closely with sales teams to identify clients' needs and develop customised solutions
In-depth research, data analysis, and statistical modelling to derive insights into market trends, pricing, and risk dynamics
Provide front office infrastructure support though ownership and maintenance of analytical libraries
Provision of expertise on quantitative methodologies, technological advancements, and industry best practices to drive innovation within the trading environment
Build and productionize Machine Learning models across asset classes, apply advanced techniques in Machine Learning, statistics, and applied mathematics using Python (PyTorch or similar) and work hands-on with cloud platforms like AWS SageMaker to scale solutions fast

Fulltime

New

Machine Learning Engineering Manager - Asset Intelligence

We’re looking for an Engineering Manager to manage a cross-functional team of Ap...

Location

United States , San Francisco

Salary:

Not provided

MaintainX

Expiration Date

Until further notice

Requirements

4+ years of engineering management experience with at least 2+ years leading high-performing AI/ML and/or applied science teams
Experience managing teams that include Fullstack Developers, AI/ML Developers and Data Scientists
Excellent communication and storytelling skills, with the ability to influence stakeholders across technical and business functions
Knowledge of modern web development frameworks (React, Node.js) and API design
Understanding of the AI/ML stack: Python, PyTorch/TensorFlow, scikit-learn, Airflow, Spark, Kubernetes, as well as JavaScript/TypeScript
Familiarity with ML/LLM ecosystems (e.g. fine-tuning, RAG, prompt orchestration, vector DBs, LlamaIndex, or similar frameworks)
Strong product instincts—able to translate ambiguous problems into measurable experiments and data products

Job Responsibility

Lead cross-functional teams of 6–10 developers across Fullstack Developers (React/Node.js), ML Developers (Python), and Data Science
Own the roadmap & technical strategy closely with Product, Design, and Engineering to scope and help teams deliver AI-powered features
Drive a culture of experimentation, applied research, and rigorous measurement—making sure we ship models that work in the real world
Lead/Grow/Coach developers on your team, help them develop new skills/experiences, advance their careers
Understand needs for your team and help enable every developer to contribute to the team's goals
Highlight the team’s impact with senior leadership
Recruit and mentor world-class AI/ML talent, building a high-performance team that can move fast and think big

What we offer

Competitive salary and meaningful equity opportunities
Healthcare, dental, and vision coverage
401(k) / RRSP enrollment program
Take what you need PTO
A Work Culture where: You’ll work alongside folks across the globe that reflect the MaintainX values: Smart Humble Optimists
We believe in meritocracy, where ideas and effort are publicly celebrated

New

Principal Data Scientist Manager

At Worldwide Learning (WWL), our mission is to inspire every person and organiza...

Location

United States , Multiple Locations

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience
OR equivalent experience
3+ years people-management experience

Job Responsibility

Lead product data insights for Microsoft internal and external skilling/learning solutions such as AI Skills Navigator to drive product improvement and better learning outcomes for users and customers
Build a global learner graph representing relationships among skills, certifications, content, modalities, and multi-step learning pathways using graph intelligence techniques (GraphRAG, embeddings, entity resolution, GNNs)
Develop, operationalize, and evolve competency models, skill taxonomies, and certification readiness frameworks to measure proficiency progression and mastery
Create multi-step journey analytics for learners, partners, and field roles using sequential modeling, trajectory prediction, and pathway optimization
Apply LLMs and multi-modal embeddings to learning content (text, transcripts, assessments) to align content to skills, outcomes, and recommended learning paths
Invent and deliver standardized metrics and KPI frameworks that quantify learning outcomes, content effectiveness, competency development, and readiness improvement
Lead A/B testing, uplift modeling, counterfactual analysis, and causal inference to evaluate the impact of learning programs, content interventions, and skilling experiences
Build model evaluation frameworks including reliability scoring, bias detection, longitudinal cohort analysis, and scenario simulation
Quantify the relationship between learning outcomes and downstream business impact such as customer success, partner readiness, deployment velocity, Azure consumption, and revenue performance
Partner with the Microsoft Partner Division, Global Partner Solutions (GPS), and Worldwide Learning to assess partner skilling, certification progress, capability gaps, and ecosystem readiness

Fulltime

New

Generative AI Validation - Senior Analyst

This position is part of the Artificial Intelligence (AI) Review and Challenge G...

Location

India , Mumbai; Bengaluru

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Advanced degree (Master’s and above) is required in the fields of mathematics, statistics, computer science, engineering, Data Science, AI/ML, etc.
6+ years’ analytics experience in financial services or related industries with minimum 2 years in Artificial Intelligence (AI) / Machine Learning (ML) area
In-depth technical knowledge of common AI/ML techniques, Generative AI, Natural Language Processing
Clear and concise written and verbal communication skills
Self-motivated and detail oriented
Demonstrated project management and organizational skills and capability to handle multiple projects at one time
Effective Stake-holder management skills

Job Responsibility

Perform independent review and conduct effective challenge across the lifecycle of Artificial Intelligence (AI) / Machine Learning (ML) non-model objects
Ensure adherence to applicable policies, procedure, templates, and testing guidance to manage the risk of all aspects of the AI/ML non-model objects
Drive constructive engagements with key stakeholders such as AI/ML Sponsors / Developers, MRM Governance, AI-CoE, Internal Audit, and regulators regarding AI/ML related matters
Support in satisfying the requirements for all internal / external regulatory exams
Develop, enhance, and validate the methods of measuring and analyzing risk, for all risk types including market, credit and operational
Support the design, development, delivery and maintenance of best-in-class Risk programs, policies and practices for Risk Management
Contribute to strategic, cross-functional initiatives within the model risk management organization
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency

What we offer

Access to telehealth options, health advocates, confidential counseling
Expanded Paid Parental Leave Policy
Programs to help manage financial well-being
Access to an array of learning and development resources
Generous paid time off packages
Resources and tools to volunteer in the communities

Fulltime

Senior AI Software Engineer

The Senior AI Software Engineer (Applications Development Technology Lead Analys...

Location

Canada , Mississauga

Salary:

120800.00 - 170800.00 USD / Year

Citi

Expiration Date

Until further notice

Requirements

6+ years of professional experience in software development with a focus on AI, machine learning, or agent-based systems
Strong proficiency in Python, SQL
Java is a plus
Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas)
Familiarity with large language models (LLMs) and their application in agentic systems
Familiarity with specific agent frameworks (e.g., LangChain, AutoGen, CrewAI, RAG) or research in multi-agent reinforcement learning
Experience in designing and implementing APIs for AI services
Experience with software development best practices, including version control (Git), CI/CD pipelines, testing, and code reviews
Excellent analytical and problem-solving skills with a creative approach to complex challenges

Job Responsibility

Design and implement intelligent agents, including their perception, reasoning, planning, and action execution modules
Develop scalable and robust architectures for agentic systems, ensuring high performance, reliability, and security
Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making
Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains
Utilize and contribute to agentic AI frameworks and development tools
Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior
Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions
Work closely with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate agentic solutions into broader products and services
Create comprehensive technical documentation for agent designs, implementations, and operational procedures
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency

Fulltime

Senior AI Data Engineer

The Senior AI Data Engineer (Applications Development Technology Lead Analyst - ...

Location

Canada , Mississauga

Salary:

120800.00 - 170800.00 USD / Year

Citi

Expiration Date

Until further notice

Requirements

6+ years of professional experience in software development with a focus on AI, machine learning, or agent-based systems
Strong proficiency in Python, SQL
Java is a plus
Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas)
Familiarity with large language models (LLMs) and their application in agentic systems
Familiarity with specific agent frameworks (e.g., LangChain, AutoGen, CrewAI, RAG) or research in multi-agent reinforcement learning
Experience in designing and implementing APIs for AI services
Experience with software development best practices, including version control (Git), CI/CD pipelines, testing, and code reviews
Excellent analytical and problem-solving skills with a creative approach to complex challenges

Job Responsibility

Design and implement intelligent agents, including their perception, reasoning, planning, and action execution modules
Develop scalable and robust architectures for agentic systems, ensuring high performance, reliability, and security
Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making
Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains
Utilize and contribute to agentic AI frameworks and development tools
Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior
Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions
Work closely with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate agentic solutions into broader products and services
Create comprehensive technical documentation for agent designs, implementations, and operational procedures
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency

Fulltime

New

Senior Data Scientist

We are looking for a hands-on Senior Data Engineer / Data Scientist to design an...

Location

United States

Salary:

110720.00 - 138400.00 USD / Year

Bugcrowd

Expiration Date

Until further notice

Requirements

5+ years of experience in Data Science, Machine Learning Engineering, or Data Engineering
Deep experience with Python, AWS services (S3, Lambda, Batch, Glue, Bedrock, Step Functions, Redshift), and ML frameworks (Scikit-Learn, XGBoost, PyTorch, etc.)
Proven experience building end-to-end ML pipelines — from data ingestion to model deployment and monitoring
Strong understanding of LLM technologies, RAG architectures, and API integration with AI systems
Ability to design and manage data architectures for large-scale, multi-tenant environments
Experience applying ML or automation to security or operational intelligence domains
A builder’s mindset — passionate about shipping scalable, practical AI systems

Job Responsibility

Design, develop, and deploy LLM- and RAG-powered applications that enhance analyst and hacker productivity across offensive security use cases
Integrate Generative AI models (e.g., via AWS Bedrock, OpenAI, Anthropic) with internal APIs and security datasets to automate and augment workflows
Build and fine-tune ML models for vulnerability prediction, triage prioritization, and exploit pattern detection
Develop evaluation pipelines and feedback loops to continuously improve AI model performance and explainability
Architect and maintain large-scale, high-performance data pipelines to process vulnerability, asset, and activity datasets from multiple sources
Build secure data ingestion, transformation, and storage workflows leveraging AWS (Glue, Lambda, Step Functions, S3, Redshift, Bedrock) and modern MLOps practices
Develop robust CI/CD pipelines for data and ML model deployment using AWS CDK and testing frameworks
Partner with infrastructure teams to scale AI workloads efficiently and securely across multi-tenant environments (FedRAMP, SOC2)
Collaborate with security researchers and engineers to translate offensive security workflows into data-driven automation
Integrate ML and AI systems with core security platforms such as the MCP server, Bugcrowd Connect, and vulnerability intelligence pipelines

Fulltime

Senior Applied Machine Learning Engineer - Asset Intelligence

MaintainX

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 18, 2026

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