senior data scientist

software engineer

data scientist

machine learning engineer

senior software engineer

ai ml computational science senior analyst

Accenture

<div>YOU ARE
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps &amp; MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
THE WORK<ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, Data Science, or a related field</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Work or coursework experience with machine learning engineering or machine learning science, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Work or coursework experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li></ul>
PREFERRED QUALIFICATION<ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li></ul></div>

AI/ML Computational Science Senior Analyst

<div>YOU ARE
As a Senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.
Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
THE WORK<ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li><li>
Experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</li><li>
Experience in building and deploying AI/ML based software to a cloud environment.</li></ul>
PREFERRED QUALIFICATION<ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li><li>
MS or PhD in related field preferred (computer science, engineering, etc.)</li></ul></div>

AI/ML Computational Science Senior Manager

Onsera Health

<div>
 
 The Challenge
 
 
 Cardiometabolic conditions will impact 80-90% of people throughout their lifetimes, representing the leading cause of death globally and an important risk factor for neurodegenerative diseases and cancer. Sustainably addressing these diseases requires breakthrough therapeutics, AI/ML innovation, and transformative business models that translate clinical outcomes into economic value.
 
 
 The Opportunity
 
 
 This is an opportunity to build the ML and AI foundations of Onsera Health's breakthrough healthcare platform. Backed by Population Health Partners (PHP)&mdash;the proven venture platform behind Metsera and Corsera Health&mdash;we're building the future of population health management.
 
 
 
 As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems.
 
 Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards.
 
 
 Responsibilities
 
 <ul>
 <li>
 
 Design and implement Onsera's agentic AI platform
 
 &ndash; architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability
 </li>
 <li>
 
 Define MLOps protocols for agentic systems
 
 &ndash; environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms
 </li>
 <li>
 
 Bridge data science and platform engineering
 
 &ndash; translate experimentation needs into GCP infrastructure, scalable compute patterns, and reproducible development environments
 </li>
 <li>
 
 Productionize data science code
 
 &ndash; convert research-grade notebooks into tested, modular, production-grade Python services, batch and streaming pipelines, and scheduled workflows
 </li>
 <li>
 
 Build production-grade data pipelines
 
 &ndash; develop idempotent, observable, and cost-efficient pipelines using BigQuery, Airflow, Google Workflows, and Cloud Run
 </li>
 <li>
 
 Implement CI/CD for ML workloads
 
 &ndash; automated validation, monitoring, rollback strategies, and model lifecycle management
 </li>
 <li>
 
 Establish reliability and governance
 
 &ndash; logging, metrics, tracing, data quality checks, and auditability for model decisions, data lineage, and agent actions
 </li>
 </ul>
 
 What We Offer
 
 <ul>
 <li>
 Mission-driven work addressing critical public health and healthcare economics challenges
 </li>
 <li>
 Ground-floor opportunity to build the ML/AI infrastructure for a breakthrough healthcare platform
 </li>
 <li>
 Partnership with a world-class team of industry leaders, innovators, technologists, bioscientists, and clinicians from PHP and beyond
 </li>
 <li>
 A fast-paced, dynamic, and highly collaborative work environment
 </li>
 <li>
 Competitive salary and benefits package, including participation in our equity program
 </li>
 </ul>
 
 
 
 
 Minimum Qualifications
 
 <ul>
 <li>
 5+ years of experience in machine learning engineering, data engineering, or a related field
 </li>
 <li>
 Strong Python engineering skills with production-quality, typed, and tested code
 </li>
 <li>
 Track record productionizing ML models in batch and/or real-time environments
 </li>
 <li>
 Hands-on experience with analytical data warehouses (BigQuery or equivalent) and workflow orchestration (Airflow or similar)
 </li>
 <li>
 Experience deploying ML systems on GCP, including Cloud Run, GCS, and IAM
 </li>
 <li>
 Infrastructure-as-Code experience (Terraform or equivalent)
 </li>
 <li>
 Experience with feature engineering, model lifecycle management, and ML evaluation
 </li>
 <li>
 Demonstrated ability to collaborate across Data Science, Product, and Platform teams
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience with LLMs, agent frameworks, or AI orchestration systems in production
 </li>
 <li>
 Familiarity with prompt management, tool calling, evaluation, and AI safety patterns
 </li>
 <li>
 Healthcare or regulated-industry experience, including familiarity with HIPAA or SOC-2 compliance
 </li>
 <li>
 Experience with claims data, EHR-derived datasets, or real-world evidence
 </li>
 <li>
 Strong written and verbal communication skills with technical and non-technical stakeholders
 </li>
 </ul>
 
 About Onsera Health
 
 
 We are an early-stage health AI company revolutionizing cardiometabolic care and population health economics connected to weight loss. Our unique position within the PHP ecosystem provides:
 
 <ul>
 <li>
 
 Venture track record:
 
 A proven track record of success in building biotech and healthcare companies
 </li>
 <li>
 
 Deep capital:
 
 Funding and resourcing to support deep tech and scientific R&amp;D&mdash;and to drive growth
 </li>
 <li>
 
 Strategic guidance:
 
 Direct access to industry pioneers (including founders of The Medicines Company and Metsera), healthcare experts (including leaders in virtual care, former FDA commissioners), strategists (McKinsey/QuantumBlack alumni), and world-class scientific talent
 </li>
 <li>
 
 Expert network:
 
 Established connections across pharma, payers, and providers
 </li>
 <li>
 
 Startup agility:
 
 Ownership in the venture, founder mentality, and ground-floor impact
 </li>
 </ul>
 
 About PHP
 
 
 Population Health Partners (PHP) is a premier investment firm established in 2020, aimed at transforming health outcomes for large populations. With offices in New York and London, PHP combines financial resources with industry-leading capabilities and technology. The firm's incubation portfolio includes Metsera and Corsera Health.
 
 
 
 Leadership:
 
 Led by industry veterans including Clive Meanwell (The Medicines Company), Chris Cox (The Medicines Company), and Whit Bernard (Metsera), bringing decades of founder experience and operational excellence in biopharma and healthcare, and Roy Berggren, 30+ year McKinsey Healthcare leader.
 
</div>

Senior Machine Learning Engineer

Compare The Market

<div>Senior Machine Learning Engineer &ndash; Customer AI
Function: Data &amp; AI Solutions
 
Location: Hybrid, London office 
Curious about what&rsquo;s next?
 
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in. 
We&rsquo;d love you to be part of our journey.
Compare the Market is building AI systems that connect directly to how millions of people in the UK find and buy financial products - and as a Senior Machine Learning Engineer, you will play a central role in making those systems production-ready. That means owning the engineering that takes ML models and AI capabilities from experimentation into reliable, scalable production use: the pipelines, the deployment tooling, the monitoring, and the shared components that make the whole thing work.
This is a hands-on role with real technical scope. You will work closely with data scientists, engineers, and product teams - contributing to architecture decisions, raising engineering standards, and building the reusable tooling that raises the pace and quality of delivery across a fast-moving and expanding set of AI capabilities and systems. 
Some of the great things you'll be doing:
ML Engineering and AI Systems
<ul><li>Own the end-to-end delivery of production machine learning and AI solutions in collaboration with data scientists and product teams
</li><li>Design and build model pipelines for training, validation, and deployment using modern tooling (e.g. MLflow, Kubernetes)
</li><li>Contribute hands-on code to model packaging, deployment, and lifecycle automation
</li><li>Build systems that monitor model performance, drift, reliability and operational health in real time
</li><li>Support both batch and real-time ML workloads depending on use case requirements
</li>Work on emerging AI and LLM-powered capabilities, helping integrate modern AI techniques into production systems where they can deliver real user value 
<li>
</li></ul>Platform and Standards
<ul><li>Help evolve our internal ML and AI platform to support experimentation, governance, and collaboration
</li><li>Define and promote best practices for ML and AI system design, including reproducibility, testing, CI/CD, model and agent observability and evaluation
</li>Develop shared tools and libraries that accelerate safe, efficient, and scalable ML development 
<li>
</li></ul>Collaboration and Technical Leadership
<ul><li>Work closely with data scientists to productionise experimental models and turn prototypes into robust services
</li><li>Act as a technical mentor and code reviewer for other engineers and contributors
</li>Provide technical leadership across ML and AI initiatives, contributing to architecture discussions and design reviews 
<li>
</li></ul>Culture and Innovation
<ul><li>Contribute to a culture of engineering excellence, collaboration, and continuous learning
</li><li>Stay up to date on emerging tools and approaches in MLOps and applied AI, helping evaluate and adopt technologies where appropriate
</li>Support responsible AI practices, contributing to explainability, auditability, and fairness in ML systems 
<li>
</li></ul>What we'd like to see from you:
The Essentials
<ul><li>Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangGraph or LangChain
</li><li>Familiarity with multi-step AI patterns - building systems where models plan, retrieve information and take sequences of actions
</li><li>Strong experience deploying ML models into production in cloud-native environments
</li><li>Solid software engineering skills in Python, with experience building scalable services, APIs, and production-quality code
</li><li>Experience with modern ML tooling and platforms (e.g. Databricks, MLflow, Airflow, Kubeflow, SageMaker, Vertex AI)
</li><li>Familiarity with CI/CD pipelines and infrastructure-as-code (e.g. Terraform, CloudFormation)
</li><li>Experience building robust, maintainable, and testable ML pipelines and APIs, including batch or real-time model delivery
</li><li>Strong understanding of ML lifecycle challenges - versioning, testing, monitoring, governance
</li>Excellent collaboration and communication skills, with experience working across data science, engineering, and product teams 
<li>
</li></ul>Nice to Have
<ul><li>Active personal use of AI-assisted or agentic coding tools, and an interest in how similar patterns could be applied to automate and accelerate ML engineering workflows - candidates who are exploring this space, even at an early stage, are encouraged to talk about it
</li><li>Experience in financial services, insurance or another regulated sector
</li><li>Experience deploying real-time or streaming ML models (e.g. Kafka, Flink, Spark Structured Streaming)
</li><li>Passion for automation, tooling, and building reusable systems
</li>Interest in responsible AI and ML model governance 
<li>
</li></ul>Why Compare the Market?
We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.</div>

Senior Machine Learning Engineer - Customer AI

International Rescue Committee

<div>The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
Job Role Overview
The Director, AI Security is a newly created senior leadership role responsible for building, leading, and continuously maturing the IRC&rsquo;s AI security function. As AI agents and AI-powered tools proliferate across the business, this role sets the organizational direction for securing AI systems &mdash; from initial design through production deployment, ongoing governance, and team development.
This is a high-visibility, cross-functional leadership role that sits at the intersection of security engineering, risk management, and emerging technology. The Director, AI Security will advise the CISO, build and develop a dedicated AI security team, own the function&rsquo;s budget, and partner with Security Operations, Identity &amp; Access Management, Governance Risk &amp; Compliance, and business unit technology teams to ensure AI adoption is secure by design.
Key Responsibilities
AI Security Strategy &amp; Governance<ul><li>
Define, own, and continuously mature the IRC's AI security strategy and program roadmap</li><li>
Establish and maintain the organization-wide AI agent registry &mdash; a governed inventory of all AI agents in production, including their purpose, permissions, data access, and accountable owners</li><li>
Develop and publish secure-by-default standards, frameworks, and reference architectures for internal AI agent development</li><li>
Create and enforce AI security policies covering agent development, deployment, monitoring, and decommissioning</li><li>
Report AI security risk posture, program progress, and emerging threats to the CISO and senior leadership on a regular cadence; serve as a key member of the security leadership team</li></ul>
Security Risk Assessment &amp; Review<ul><li>
Coordinate and perform GIS security reviews within the organization's AI governance framework, ensuring AI platforms, agents, and use cases receive appropriate security assessment and approval prior to production deployment.</li><li>
Partner with AI Governance, Privacy, Legal, and Technology stakeholders to support the AI intake, assessment, and stage-gating process, providing security expertise, control requirements, and risk-based recommendations throughout the solution lifecycle.</li><li>
Perform security risk assessments and classify AI platforms, agents, and use cases according to the approved risk-tiering model, applying review, control, and approval requirements proportionate to risk.</li><li>
Conduct a structured controls assessment for every use case, validating that mandatory security baseline requirements are met &mdash; including least-privilege access, credential management, audit logging, data minimization, human-in-the-loop checkpoints, and kill switch capability</li><li>
Issue formal, documented approval decisions for every reviewed use case &mdash; Approved, Approved with Conditions, or Not Approved &mdash; with a full written rationale recorded in the AI agent registry to maintain an auditable approval history</li><li>
Manage defined SLA timelines for all reviews (Tier 1: 5 business days, Tier 2: 10 business days, Tier 3: 15 business days) to ensure security review does not become a blocker to business unit velocity</li><li>
Conduct periodic reassessments of all active agents on a risk-appropriate cycle &mdash; annually for Tier 1, semi-annually for Tier 2, and quarterly for Tier 3 &mdash; and trigger immediate out-of-cycle reviews whenever a material change is made to an agent's capabilities, data access, or toolset</li><li>
Monitor the evolving AI threat landscape on an ongoing basis and proactively assess whether newly discovered attack techniques &mdash; including new prompt injection methods, jailbreaks, or model-specific vulnerabilities &mdash; expose any currently approved use cases, initiating remediation where required</li><li>
Lead post-incident reassessments for any active agent involved in a security incident, updating the agent's approval status and controls requirements based on findings</li><li>
Evaluate third-party AI tools, models, and platforms for security risk prior to organizational adoption</li><li>
Maintain a risk register specific to AI systems, tracking identified vulnerabilities, mitigations, and residual risk</li><li>
Report aggregate review metrics to the CISO on a regular cadence &mdash; including number of use cases reviewed, approval rates by tier, common findings, and AI risk distribution across business units &mdash; providing organizational visibility into the AI risk posture</li></ul>
Technical Oversight &amp; Controls<ul><li>
Define technical security requirements for AI agents including least-privilege access, prompt injection defenses, output filtering, audit logging, and human-in-the-loop controls</li><li>
Build, lead, and develop a team of AI security engineers responsible for implementing and validating controls across the AI agent development lifecycle</li><li>
Own and resource red team and adversarial testing programs targeting AI systems, ensuring adequate coverage through the AI Red Team Engineer and contracted specialists</li><li>
Drive adoption of secure coding practices and security tooling within AI development workflows</li></ul>
Identity &amp; Data Security Coordination<ul><li>
Establish governance frameworks with the IAM team to ensure AI agent identities, service accounts, and credentials are provisioned and governed under least-privilege principles across the organization</li><li>
Set data security standards with the ML/Data Security Analyst to ensure sensitive data &mdash; including PII, PHI, and proprietary information &mdash; is handled correctly throughout AI agent workflows, and hold teams accountable to those standards</li><li>
Define data classification requirements for information flowing through AI systems, including what data may and may not be included in model context</li></ul>
Incident Response<ul><li>
Develop and maintain AI-specific incident response runbooks covering scenarios such as prompt injection attacks, rogue agent behavior, credential compromise, and data leakage via AI systems</li><li>
Serve as executive sponsor and escalation point for significant AI-related security incidents, ensuring the organization maintains a tested, capable incident response function</li><li>
Conduct post-incident reviews and drive lessons learned back into the AI security program</li></ul>
Regulatory &amp; Compliance Alignment<ul><li>
Serve as the organization's primary subject matter expert on AI-specific regulatory requirements including the EU AI Act, NIST AI Risk Management Framework (AI RMF), GDPR as applied to AI systems, and emerging regional AI legislation</li><li>
Partner with the GRC team to map AI security controls to compliance obligations and maintain evidence for audits</li><li>
Monitor the evolving AI regulatory landscape and proactively advise leadership on upcoming obligations</li></ul>
People Leadership &amp; Team Development<ul><li>
Recruit, hire, onboard, and develop a high-performing AI security team, including AI security engineers, a red team engineer, and a data/ML security analyst</li><li>
Set clear team goals, conduct regular performance reviews, and create development plans that grow individual skills and advance careers</li><li>
Foster a team culture of continuous learning, given the rapidly evolving AI threat landscape, and ensure team members maintain current expertise in AI security techniques and tooling</li></ul>
Vendor Management<ul><li>
Lead vendor evaluation and selection for AI security tooling, negotiating contracts and managing ongoing relationships with key security vendors and managed service providers</li><li>
Develop a multi-year AI security roadmap aligned to IRC risk appetite, and evolving regulatory obligations</li></ul>
Working Relationships
Internal:<ul><li>
CISO, ITLT, Security Operations &amp; Engineering lead and team, Identity &amp; Access Management (IAM) lead and team, Governance, Risk &amp; Compliance (GRC) lead, AI Review Panel lead and team, Office of General Council team, AI &amp; Program tech engineering and team, Data Architecture lead and engineering Team</li></ul>
External:<ul><li>
AI and Security Vendors &mdash; ongoing for product evaluation, contracts, and threat intel</li><li>
Industry Peers &amp; Research Communities &mdash; active participation in ISACs, working groups, and conferences</li></ul>
Required Qualifications
Education<ul><li>
Bachelor's degree in Computer Science, Information Security, Cybersecurity, or a related technical field</li><li>
Advanced degree (Master's or equivalent) preferred but not required where experience is demonstrably strong</li></ul>
Experience<ul><li>
10+ years of experience in information security, with at least 4-5 years in a people management or senior security leadership role</li><li>
Demonstrated hands-on experience securing AI/ML systems, LLM-based applications, or agentic AI workflows</li><li>
Proven experience conducting threat modeling, security architecture reviews, and risk assessments for complex, distributed systems</li><li>
Experience building and leading security teams, including hiring, developing, and retaining talent in a fast-moving technical domain</li><li>
Track record of working cross-functionally with engineering, product, legal, and compliance teams; experience owning and managing a security budget including tooling, vendor, and headcount decisions</li><li>
Prior experience with incident response and managing security incidents involving automated or AI-driven systems is strongly preferred</li><li>
Demonstrated experience managing and developing a team of security professionals, including hiring, performance management, and career development</li></ul>
This is a remote position open to internal candidates based in countries where IRC operates who have the right to work in their location. Successful candidates will be hired on a local employment contract and according to local salary scale.
Compensation: (US Pay Range: $158,492-$184,536/yr; UK Pay Range: &pound;77,499-&pound;93,814/yr) Posted pay ranges apply to US-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements. 
PROFESSIONAL STANDARDS
All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way - Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients.
Cookies: https://careers.rescue.org/us/en/cookiesettings
Compensation: Posted pay ranges apply to US-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements.
US Benefits: We offer a comprehensive and highly competitive set of benefits. In the US, these include: 10 sick days, 10 US holidays, 20-25 paid time off days depending on role and tenure, medical insurance starting at $163 per month, dental starting at $6.50 per month, and vision starting at $5 per month, FSA for healthcare and commuter costs, a 403b retirement savings plans with immediately vested matching, disability &amp; life insurance, and an Employee Assistance Program which is available to our staff and their families to support counseling and care in times of crisis and mental health struggles.
Equal Opportunity Employer: IRC is an Equal Opportunity Employer. IRC considers all applicants on the basis of merit without regard to race, sex, color, national origin, religion, sexual orientation, age, marital status, veteran status, disability or any other characteristic protected by applicable law.
#li-1</div>

Director, AI Security

Faculty

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<h2 class="jobSectionHeader"> 
About the team</h2><div> 
</div>Our Public Services Business Unit is committed to leveraging AI for the benefit of individual citizens and the public good. 
 
From our work informing strategic government decisions, to optimising our NHS, through to reducing bureaucratic backlogs - we know that AI offers opportunities to drive improvements at every level of Government and we are proud to lead on some of the most impactful work happening in the sector. 
 
Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Security Clearance (SC) and willing to work on site with these clients from time to time.<h2 class="jobSectionHeader">
About the role</h2>
As a Lead AI/ML Engineer at Faculty, you will set the technical direction for complex AI/ML projects, ensuring models perform at scale and in production over time by balancing technical trade-offs and guiding team priorities.
You will lead the delivery of large-scale AI-powered platforms in high-risk environments while defining project roadmaps across multiple complex workstreams. 
 
This is an ambitious, entrepreneurial leadership role where you will act as a trusted technical expert, defending your architectural rationale to senior stakeholders to ensure we deliver high-quality, high-value outputs.<div></div><div> 
</div><h2 class="jobSectionHeader">
What you'll be doing:</h2><ul><li> 
Setting the technical direction for complex software projects to ensure architectural decisions support long-term product and client goals.</li><li>
Driving the development of shared software libraries and microservices that accelerate delivery across multiple client engagements.</li><li>
Overseeing the delivery of large-scale AI-powered platforms while defining project roadmaps in high-risk environments.</li><li>
Facilitating alignment between ML, Data Science, and DevOps crafts to ensure agentic software is built on a reliable foundation.</li><li>
Managing and coaching a distributed team of engineers, setting development goals that align with organisational growth.</li><li>
Establishing enterprise-wide standards for code delivery, testing, and system documentation across the software engineering craft.</li><li>
Leading hiring processes for the software engineering craft to continue building a world-class technical team.</li></ul><div></div><div> 
</div><h2 class="jobSectionHeader">
Who we're looking for:</h2><ul><li> 
You apply deep expertise across the application lifecycle to set high standards for system integration and end-user software quality.</li><li>
You design large-scale, complex software ecosystems with the authority to justify critical architectural trade-offs in high-stakes environments.</li><li>
You define the gold standard for production readiness, establishing application deployment protocols across diverse client engagements.</li><li>
You translate high-level commercial strategy into technical roadmaps, ensuring AI work-streams are accurately estimated and seamlessly integrated.</li><li>
You architecturally direct the development of products leveraging autonomous AI agents to ensure they are robust and effectively integrated.</li><li>
You are a confident communicator, capable of conveying complex technical roadmaps and architectural risks to commercial partners and executive leadership.</li></ul><h2 class="jobSectionHeader">
The Interview Process</h2><div></div><ul><li> 
Talent Team Screen (30 minutes)</li><li>
Introduction to the Hiring Manager (30 minutes)
</li><li>Pair Programming Interview (90 minutes)
</li><li>System Design Interview (90 minutes)
</li><li>Commercial &amp; Leadership Interview (60 minutes)</li></ul><div></div> 
#LI-PRIO<h2 class="jobSectionHeader">
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Lead Software Engineer

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Alexa for Shopping, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. 
 
This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing data analysis, statistical modeling, machine learning (ML) technologies, and experimentation to drive product decisions and optimize customer experiences. 
 
Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. 
 
Key job responsibilities 
Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that will shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include designing experiments, analyzing results, and launching new features, products and systems. 
 
A day in the life 
Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. Use statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on a rich set of structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. 
 
About the team 
The Alexa for Shopping Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the AfS AI, from making it agentic, enabling customers to set price alerts or empower AfS to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Master's degree or above in Math, Statistics, Computer Science, or related science field</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance</li><li>Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2</li><li>Experience working on multi-team, cross-disciplinary projects</li></ul> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Data Scientist II, Alexa for Shopping Science UK, Alexa for Shopping Science UK

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