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Our client is an innovative AI avatar technology company powering the visual and embodiment layer for AI personas. Their proprietary framework brings AI to life as fully realized digital identities that look, think, and behave like living entities across enterprise, gaming, and entertainment ecosystems. Backed by $200M from top-tier investors, they are built on the belief that every website, app, game, and human will soon have an AI persona.

We are seeking a Senior Machine Learning Engineer to join their Avatar Technology team. In this role, you will bridge the gap between machine learning and real-time animation pipelines, taking generative models from prototype to high-quality production environments.

What You’ll Do

• Production ML Integration: Integrate machine learning models into real-time animation systems across mobile and web environments.
• Motion Generation: Develop systems that translate inputs like audio, text, and intent into responsive avatar motion, specifically adapting generative models (diffusion, transformers) for facial animation and gesture generation.
• Data & Tooling Pipelines: Build motion data processing pipelines (mocap, facial capture) and develop DCC tool integrations (Maya, Blender) to empower Technical Artists.
• Optimization & Collaboration: Partner with Behavior and LLM teams to link predictive motion to character logic , while optimizing performance across CPU, GPU, and memory constraints.

What You Should Have

• 7+ years of experience in machine learning, animation systems, or related technical roles within games, VFX, or interactive media.
• Strong programming skills in Python, along with C++ and/or C#.
• Production experience with ML frameworks like PyTorch or TensorFlow , and a proven track record of shipping ML systems.
• Practical exposure to skeletal animation, rigging, or simulation pipelines.
• Experience integrating systems into real-time engines such as Unity, Unreal, or web-based runtimes.
• Deep understanding of performance constraints including latency, memory, and scalability.

Benefits & Structure

• Work Structure: Hybrid environment (minimum 4 days weekly in-office); remote-eligible
• Compensation: Competitive salary, equity packages, and comprehensive health/wellness benefits.
• Perks: Unlimited PTO and parental leave.

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Senior / Staff Software Engineer

Location: Costa Mesa, CA (Hybrid – minimum 3 days onsite)

Base Salary: $190,000 – $220,000+

Visa Sponsorship: Not available

Responsibilities

• Design and build real‑time streaming and batch data systems
• Own core platform architecture and implementation
• Modernize and scale data lake infrastructure
• Ensure high availability, observability, and reliability
• Partner with analytics, hardware, and engineering teams

Technical Focus

• Real‑time streaming pipelines (Kafka, Flink)
• Distributed compute (Spark)
• Backend services on top of data platforms
• Platform reliability and operational tooling

Experience & Requirements

• 6+ years of software engineering experience
• Strong background in data platforms and distributed systems
• Experience owning data lake or platform architecture
• Proficiency in:
• Python
• SQL
• Java or Scala
• Spark
• Kafka or Flink

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DevSecOps Manager

Location: Remote (EST/CST)
Pay: $200k – $250k Base + Bonus & Equity

Overview:

A global, high-scale data and analytics platform is seeking a Senior Manager, DevSecOps to lead multiple teams focused on embedding security across modern engineering environments. This organisation operates at massive scale, processing billions of real-time events daily, and partners with leading global brands.
This role blends deep technical leadership with strategic oversight, driving secure DevOps, cloud-native security, and AI/ML security initiatives. You’ll play a critical role in shaping secure software delivery and AI lifecycle governance across the business.

Responsibilities:

• Lead and mentor multiple DevSecOps and security engineering teams across infrastructure and platform environments
• Define and execute DevSecOps strategy, including CI/CD, IaC security, and cloud-native architectures
• Implement and oversee security controls for AI/ML pipelines, including protection against model and data threats
• Establish governance frameworks for AI security, including policies, risk management, and compliance practices
• Drive automation of security tooling across pipelines (SAST, DAST, SCA, and AI artefact scanning)
• Design scalable security architectures across distributed systems and cloud platforms
• Lead incident response for security events, including AI-specific threat scenarios
• Partner with senior stakeholders to align security initiatives with broader business objectives
• Establish KPIs and metrics to track security posture, risk exposure, and team performance

Must Have Qualifications:

• 5-6+ years of experience in DevSecOps, DevOps, or Cybersecurity, including team leadership
• Strong expertise in cloud security (AWS, GCP, or OCI), CI/CD pipelines, and Infrastructure-as-Code (Terraform, Ansible, etc.)
• Hands-on experience with application and container security (Kubernetes, Docker, SAST/DAST/SCA tools)
• Exposure to AI/ML security concepts (LLMs, model security, or pipeline security)
• Experience with compliance frameworks (SOC 2, ISO 27001, SOX)
• Bachelor’s degree in Computer Science, Information Systems, or equivalent experience

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Staff Engineer (AI)
£150,000 – £170,000 + benefits
London (Hybrid)
This is a great opportunity to join a high‑growth, PE‑backed organisation where you can take ownership of building and scaling an AI‑native data platform from the ground up.

THE COMPANY:

The group’s mission is to unify their businesses into a single, powerful data platform, creating comprehensive global datasets. With strong funding and a clear acquisition strategy, they are building a category‑defining B2B data business.

THE ROLE:

You will take ownership of building and rapidly iterating on core platform features as part of a highly agile engineering team. Key responsibilities include:

• Developing and shipping working prototypes within days
• Building and improving data platform components and internal tools
• Turning complex data assets into user‑ready products
• Collaborating with senior engineers and leadership on architecture decisions
• Helping modernise and scale early‑stage prototypes into production systems

YOUR SKILLS AND EXPERIENCE:

You will bring strong capability in:

• Strong experience in Python, SQL, and TypeScript
• Hands‑on software engineering experience
• Proven ability to build and deliver products quickly in fast‑paced environments
• Experience working with data‑heavy systems or platforms
• Solid understanding of modern engineering practices

THE BENEFITS:

You will receive a salary of £150,000 – £170,000 depending on experience, along with a comprehensive benefits package and the opportunity to shape a high‑impact AI platform from day one.

HOW TO APPLY:

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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To Apply for this Job Click Here

The Role

We are looking for a Technical Architect to take joint ownership of two critical dimensions: shaping the architecture of our platform and providing hands-on technical leadership to our engineering team. You will be a key decision-maker in how we build, scale, and evolve our systems – balancing technical excellence with practical delivery.
You will work closely with engineering, AI/ML, and product teams, and you will have a direct impact on the technology roadmap of a fast-growing startup in a highly regulated and meaningful space.

Responsibilities

Systems Architecture

• Design and evolve the overall platform architecture – backend services, ML inference pipelines, and clinical integrations – ensuring scalability, security, and performance.
• Define and enforce architectural patterns, coding standards, and technology decisions with a long-term perspective.
• Evaluate and select technologies, frameworks, and tools, clearly articulating trade-offs to both technical and non-technical stakeholders.
• Ensure architecture decisions account for the regulatory requirements of the medical device space (MDR, FDA SaMD).
• Lead the technical design of integrations with hospital systems (PACS, HIS) using standards such as DICOM and HL7/FHIR.
• Own non-functional requirements: reliability, latency, data privacy (GDPR, HIPAA-aligned), and disaster recovery.

Technical Leadership

• Be the technical reference for the engineering team: code reviews, mentoring, and establishing engineering best practices.
• Collaborate with the AI/ML team on the productionisation of inference models and the optimization of the end-to-end ML pipeline.
• Contribute to sprint planning and technical estimation, helping the team break down complexity into deliverable increments.
• Proactively identify and mitigate technical risks, communicating them clearly before they become blockers.
• Foster an engineering culture centred on quality, automation, observability, and continuous improvement.

Requirements

Must-haves

• 5-8 years of software engineering experience, with at least 2-3 years in architecture or senior technical leadership roles.
• Proven experience designing and operating cloud-native systems on AWS (compute, storage, networking, managed services, IAM).
• Strong background in Python for production environments – APIs, data processing pipelines, and ML model integration.
• Solid understanding of containerisation (Docker) and orchestration in production environments.
• Deep knowledge of distributed systems design principles: microservices, event-driven architecture, API design, and data consistency patterns.
• Experience building CI/CD pipelines and driving DevOps practices across an engineering team.
• Ability to document and communicate architecture decisions clearly, both in writing and in technical discussions.
• Comfortable operating in a startup environment: autonomous, pragmatic, and able to balance ideal solutions with real constraints.

Nice-to-haves

• Experience deploying and optimising ML models in production – including ONNX Runtime or similar inference frameworks.
• Familiarity with medical imaging standards: DICOM, HL7, FHIR.
• Background in regulated environments (MDR, FDA 21 CFR Part 11, ISO 13485, or similar).
• Experience with MLOps practices: model versioning, drift monitoring, and retraining pipelines.
• Knowledge of PHP/Laravel or experience working with and evolving an existing codebase built on it.
• Prior experience in healthtech, medtech, or other highly regulated industries.

What We Offer

• Competitive salary aligned with your experience and the market.
• Hybrid model with real flexibility – we care about outcomes, not hours.
• Direct, visible impact: your work shapes tools that help clinicians make better diagnoses.
• Small, highly skilled team with strong technical autonomy.
• Annual budget for training, conferences, and certifications.
• Freedom to challenge the status quo and propose improvements to how we build things.
• A collaborative, mission-driven environment where engineering is taken seriously.

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Analytics Engineer (12-month FTC)

£70,000 – £90,000

Remote (UK Based – meets in Farringdon, London once every 6 months)

A unique opportunity to step into a high-impact Analytics Engineer role within a purpose-driven organisation using data to improve real-world outcomes. This position offers the chance to take ownership of critical data models and pipelines, working in a modern cloud data stack while collaborating closely with engineering and analytics teams. You will play a key role in ensuring continuity across core data products while contributing to new development.

THE COMPANY

They are an e-Health provider operating within a highly regulated, data-rich environment. Focused on delivering meaningful outcomes at scale, they combine clinical expertise with modern data capabilities to continuously improve services. Their data function is central to decision-making, with a strong emphasis on quality, governance, and impact. The team is collaborative, remote-first, and values thoughtful, well-engineered solutions.

THE ROLE

As an Analytics Engineer you will step into an established Analytics Engineering function, maintaining momentum across critical projects while contributing to the ongoing development of the data platform.

Specifically, you can expect to be involved in the following:

• Take ownership of in-flight data projects, ensuring successful delivery and continuity.
• Design, build, and maintain dbt models including fact and dimension tables and semantic layers.
• Support the development of scalable data models with clear structure and strong data governance.
• Collaborate with data engineers to evolve pipelines across the data lifecycle.
• Review and improve SQL and modelling best practices across the analytics team.
• Contribute to the transition from prototype analysis to production-grade data assets.
• Ensure documentation and handover processes are clear and well-structured.

SKILLS AND EXPERIENCE

The successful Analytics Engineer will have the following skills and experience:

• Strong commercial experience working with dbt, including building models and implementing testing frameworks.
• Advanced SQL skills with experience working in modern cloud data environments.
• Solid understanding of data modelling principles including star schema design and data grain.
• Experience working with Python in a data context.
• Ability to collaborate across teams and influence technical decisions constructively.
• Comfortable working within structured, governed data environments
• Desirable experience includes exposure to Databricks, CI/CD workflows, or regulated industry data, though this is not essential.

BENEFITS

The successful Analytics Engineer will receive the following benefits:

• Salary between £70,000 – £90,000 – depending on experience

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Analytics Engineer (12-month FTC)

£70,000 – £90,000

Remote (UK Based – meets in Farringdon, London once every 6 months)

A unique opportunity to step into a high-impact Analytics Engineer role within a purpose-driven organisation using data to improve real-world outcomes. This position offers the chance to take ownership of critical data models and pipelines, working in a modern cloud data stack while collaborating closely with engineering and analytics teams. You will play a key role in ensuring continuity across core data products while contributing to new development.

THE COMPANY

They are an e-Health provider operating within a highly regulated, data-rich environment. Focused on delivering meaningful outcomes at scale, they combine clinical expertise with modern data capabilities to continuously improve services. Their data function is central to decision-making, with a strong emphasis on quality, governance, and impact. The team is collaborative, remote-first, and values thoughtful, well-engineered solutions.

THE ROLE

As an Analytics Engineer you will step into an established Analytics Engineering function, maintaining momentum across critical projects while contributing to the ongoing development of the data platform.

Specifically, you can expect to be involved in the following:

• Take ownership of in-flight data projects, ensuring successful delivery and continuity.
• Design, build, and maintain dbt models including fact and dimension tables and semantic layers.
• Support the development of scalable data models with clear structure and strong data governance.
• Collaborate with data engineers to evolve pipelines across the data lifecycle.
• Review and improve SQL and modelling best practices across the analytics team.
• Contribute to the transition from prototype analysis to production-grade data assets.
• Ensure documentation and handover processes are clear and well-structured.

SKILLS AND EXPERIENCE

The successful Analytics Engineer will have the following skills and experience:

• Strong commercial experience working with dbt, including building models and implementing testing frameworks.
• Advanced SQL skills with experience working in modern cloud data environments.
• Solid understanding of data modelling principles including star schema design and data grain.
• Experience working with Python in a data context.
• Ability to collaborate across teams and influence technical decisions constructively.
• Comfortable working within structured, governed data environments
• Desirable experience includes exposure to Databricks, CI/CD workflows, or regulated industry data, though this is not essential.

BENEFITS

The successful Analytics Engineer will receive the following benefits:

• Salary between £70,000 – £90,000 – depending on experience

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Analytics Engineer (12-month FTC)

£70,000 – £90,000

Remote (UK Based – meets in Farringdon, London once every 6 months)

A unique opportunity to step into a high-impact Analytics Engineer role within a purpose-driven organisation using data to improve real-world outcomes. This position offers the chance to take ownership of critical data models and pipelines, working in a modern cloud data stack while collaborating closely with engineering and analytics teams. You will play a key role in ensuring continuity across core data products while contributing to new development.

THE COMPANY

They are an e-Health provider operating within a highly regulated, data-rich environment. Focused on delivering meaningful outcomes at scale, they combine clinical expertise with modern data capabilities to continuously improve services. Their data function is central to decision-making, with a strong emphasis on quality, governance, and impact. The team is collaborative, remote-first, and values thoughtful, well-engineered solutions.

THE ROLE

As an Analytics Engineer you will step into an established Analytics Engineering function, maintaining momentum across critical projects while contributing to the ongoing development of the data platform.

Specifically, you can expect to be involved in the following:

• Take ownership of in-flight data projects, ensuring successful delivery and continuity.
• Design, build, and maintain dbt models including fact and dimension tables and semantic layers.
• Support the development of scalable data models with clear structure and strong data governance.
• Collaborate with data engineers to evolve pipelines across the data lifecycle.
• Review and improve SQL and modelling best practices across the analytics team.
• Contribute to the transition from prototype analysis to production-grade data assets.
• Ensure documentation and handover processes are clear and well-structured.

SKILLS AND EXPERIENCE

The successful Analytics Engineer will have the following skills and experience:

• Strong commercial experience working with dbt, including building models and implementing testing frameworks.
• Advanced SQL skills with experience working in modern cloud data environments.
• Solid understanding of data modelling principles including star schema design and data grain.
• Experience working with Python in a data context.
• Ability to collaborate across teams and influence technical decisions constructively.
• Comfortable working within structured, governed data environments
• Desirable experience includes exposure to Databricks, CI/CD workflows, or regulated industry data, though this is not essential.

BENEFITS

The successful Analytics Engineer will receive the following benefits:

• Salary between £70,000 – £90,000 – depending on experience

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Analytics Engineer (12-month FTC)

£70,000 – £90,000

Remote (UK Based – meets in Farringdon, London once every 6 months)

A unique opportunity to step into a high-impact Analytics Engineer role within a purpose-driven organisation using data to improve real-world outcomes. This position offers the chance to take ownership of critical data models and pipelines, working in a modern cloud data stack while collaborating closely with engineering and analytics teams. You will play a key role in ensuring continuity across core data products while contributing to new development.

THE COMPANY

They are an e-Health provider operating within a highly regulated, data-rich environment. Focused on delivering meaningful outcomes at scale, they combine clinical expertise with modern data capabilities to continuously improve services. Their data function is central to decision-making, with a strong emphasis on quality, governance, and impact. The team is collaborative, remote-first, and values thoughtful, well-engineered solutions.

THE ROLE

As an Analytics Engineer you will step into an established Analytics Engineering function, maintaining momentum across critical projects while contributing to the ongoing development of the data platform.

Specifically, you can expect to be involved in the following:

• Take ownership of in-flight data projects, ensuring successful delivery and continuity.
• Design, build, and maintain dbt models including fact and dimension tables and semantic layers.
• Support the development of scalable data models with clear structure and strong data governance.
• Collaborate with data engineers to evolve pipelines across the data lifecycle.
• Review and improve SQL and modelling best practices across the analytics team.
• Contribute to the transition from prototype analysis to production-grade data assets.
• Ensure documentation and handover processes are clear and well-structured.

SKILLS AND EXPERIENCE

The successful Analytics Engineer will have the following skills and experience:

• Strong commercial experience working with dbt, including building models and implementing testing frameworks.
• Advanced SQL skills with experience working in modern cloud data environments.
• Solid understanding of data modelling principles including star schema design and data grain.
• Experience working with Python in a data context.
• Ability to collaborate across teams and influence technical decisions constructively.
• Comfortable working within structured, governed data environments
• Desirable experience includes exposure to Databricks, CI/CD workflows, or regulated industry data, though this is not essential.

BENEFITS

The successful Analytics Engineer will receive the following benefits:

• Salary between £70,000 – £90,000 – depending on experience

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here