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Platform Systems Architect

Dallas, TX (Onsite, 5 days per week)
Base Salary: $200,000 – 225,000

Overview

A technology manufacturer is expanding its infrastructure footprint significantly, investing largely into domestic capacity and digital platform growth. This role is central to building and evolving the internal enterprise platform that supports that expansion.

This position focuses on developing an internal, cloud platform that enables application and engineering teams to build, deploy, and run services across a hybrid environment that spans on premises data centers and public cloud.

The Role

Seeking a senior Platform Systems Architect to define and design the foundational infrastructure platform that internal teams depend on. This is a senior individual contributor role responsible for end to end platform architecture across compute, storage, networking, and core platform services.

You will work across both on premises and public cloud environments to deliver a unified, scalable, and reliable platform. This is a hands-on architecture role, suited for someone who has designed and built large distributed systems, not just documented or managed them.

What You Will Do

• Design end to end platform architectures across compute, storage, networking, and platform services
• Define and maintain enterprise standards, reference architectures, and design patterns
• Architect hybrid environments spanning data centers and public cloud platforms
• Design and support Kubernetes based platforms (OpenShift, Rancher, or similar)
• Drive Infrastructure as Code using Terraform and/or Ansible
• Establish CI/CD, automation, and DevOps platform standards
• Design observability and reliability solutions using tools like Grafana, Prometheus, and ELK
• Partner with engineering teams to modernize legacy systems into distributed architectures
• Provide technical leadership as a senior individual contributor

Required Qualifications

• 7+ years in systems architecture, platform engineering, or infrastructure engineering
• Experience designing and operating large scale distributed systems
• Strong expertise across compute, storage, and networking
• Hands-on Kubernetes experience (OpenShift, Rancher, or equivalent)
• Experience with Terraform and/or Ansible
• Proven hybrid cloud experience (on prem + public cloud)
• Familiarity with CI/CD and DevOps practices
• Experience with observability tools (Grafana, Prometheus, ELK stack)
• Working knowledge of Python or Go

Preferred Qualifications

• Experience building a private cloud or internal platform from the ground up
• Advanced networking experience (EVPN, VXLAN, SDN)
• Experience with data or streaming platforms (Kafka, Spark)
• Knowledge of API gateways, IAM, and platform integration patterns
• Exposure to GPU, AI, or high performance computing workloads
• Hands-on experience with major public cloud platforms

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Principal Data Scientist – GenAI & Personalization – Remote (US) | $190k-$220k + 15% bonus

My client is a large, mission-driven learning technology organization reinventing itself as an AI‑first platform. Generative AI, personalization, and data science are now at the core of how millions of students learn – and they’re hiring a Principal Data Scientist to lead from the front.

This is a true hands-on principal IC role: deep technical ownership, real influence, no line management.

Why this role stands out

• Own and shape a core AI capability – scope built around your strengths
• Work on customer-facing GenAI products used at massive scale
• Strong leadership air cover – minimal meetings, protected focus time
• High-visibility work with real-world impact in education

What you’ll do

• Design and build GenAI systems that translate education standards into structured learning objectives
• Improve AI-driven assessments, content generation, and personalization engines
• Apply rigorous statistics to messy human data – and make it production-ready
• Partner closely with engineering on deployment, testing, and optimization

What they’re looking for

• PhD in Statistics or a highly quantitative field
• Strong generative AI experience (personalization or content generation a big plus)
• Excellent Python and end-to-end ownership – research → production → impact
• Clear communicator who can influence both technical and non-technical teams
• 4-5 years post-PhD industry experience

Bonus points for: MLOps, AWS/Databricks, or education experience (not required)

Logistics

• Fully remote (US-based)
• US Citizen or Green Card only (no sponsorship)
• Core availability: 11am-5pm EST

If you want principal-level ownership, meaningful scale, and the chance to define how GenAI shows up in real learning products – this role is built for that.

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Staff Data Scientist (GTM) | EU Remote

I’m partnering with a fast-growing B2B SaaS company on a high-impact Staff Data Scientist hire within their GTM Data function.

This is a rare role where you’re not just building models – you’re shaping how a business understands its customers. You’ll own the full lifecycle from problem framing through to production, and have a genuine seat at the table with senior leadership.

‘ :

* Building LTV and churn models that drive retention, upsell, and cross-sell strategy

* Developing predictive expansion models tied directly to revenue outcomes

* Bringing causal inference and Marketing Mix Modelling thinking to strategic marketing decisions

* Coaching analysts and embedding best practices across the team

‘ :

* 6+ years in applied data science

* Strong ML chops – churn, segmentation, LTV modeling

* B2B SaaS background (strongly preferred)

* Python + SQL as core tools

* At least one ML model shipped to production

* Someone who connects technical work to business outcomes – not just a list of tools on a CV

:

* Your experience is purely MMM or econometrics

* You’re heavily focused on LLMs/RAG

* You prefer a heavily structured environment with lots of oversight

UK Citizens and EU Citizens only.

If this sounds like your next move – or someone you know – drop me a message or comment below. Happy to share more details confidentially.

#DataScience #MachineLearning #SaaS #Hiring #DataJobs #LTV #ChurnModeling #RemoteJobs

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Senior Analytics Engineer – Orange County, CA $150,000 – $200,000 + Equity

We’re partnering with a fast-growing, product-driven technology company that is building a modern, data-first organization. They’re looking for a Senior Analytics Engineer to play a critical role in shaping how data is modeled, transformed, and consumed across the business.

This is an opportunity to work at the intersection of data engineering and analytics, helping stakeholders make smarter, faster decisions by delivering clean, scalable, and reliable data models.

What You’ll Do

• Design and build scalable data models that power analytics, reporting, and product insights
• Transform raw data into high-quality, well-documented datasets using modern tooling (e.g., dbt, SQL, cloud warehouses)
• Partner with product, engineering, and business teams to define key metrics and data requirements
• Improve data quality, testing, and governance across the analytics layer
• Enable self-service analytics by creating clear, intuitive datasets and documentation
• Contribute to the overall data architecture and best practices

What We’re Looking For

• 5+ years of experience in analytics engineering, data engineering, or a related field
• Strong SQL skills and experience building data models in a modern warehouse (Snowflake, BigQuery, Redshift, etc.)
• Hands-on experience with dbt or similar transformation frameworks
• Strong understanding of data modeling concepts (dimensional modeling, star schemas, etc.)
• Experience working closely with cross-functional stakeholders
• Familiarity with BI tools (Looker, Tableau, or similar)
• A strong focus on data quality, testing, and maintainability

Nice to Have

• Experience with Python or other scripting languages
• Exposure to event-based data or product analytics
• Experience in high-growth or startup environments

Why Join?

• High-impact role with real ownership over the analytics layer
• Collaborative, data-driven culture
• Competitive compensation: $150K-$200K base + equity
• Opportunity to shape the future of data within a scaling organization

If you’re excited about building clean data models, enabling better decision-making, and working in a high-growth environment – this is a great opportunity to step into a highly visible role.

Feel free to reach out directly or apply here to learn more.

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Senior Director, eCommerce Engineering

Mountain View, CA | Hybrid

We are partnering with a global consumer technology company that serves hundreds of millions of users through subscription-based digital products and services.

As the organization continues to invest in platform modernization and AI-driven innovation, they are looking to add a Senior Director of eCommerce Engineering to help shape the future of their global commerce ecosystem.

The Opportunity

This is a highly visible engineering role focused on modernizing enterprise commerce platforms, influencing long-term architecture strategy, and accelerating AI adoption across engineering teams.

You will partner closely with engineering leaders, architects, and product stakeholders to improve platform reliability, performance, and developer productivity while helping define the next generation of customer-facing commerce experiences.

What You’ll Be Doing

* Guide architecture strategy across enterprise commerce platforms.
* Drive modernization efforts across legacy Java-based backend systems.
* Improve checkout, billing, subscription, and payments infrastructure.
* Partner with engineering leaders and architects across globally distributed teams.
* Influence cloud, platform, and database modernization initiatives.
* Introduce AI-enabled capabilities across engineering workflows and platform experiences.
* Improve platform reliability, scalability, and operational efficiency.
* Define long-term technical roadmaps and engineering standards.

What We’re Looking For

* Experience building and developing engineering organizations within consumer technology environments.
* Strong background in backend architecture and distributed systems.
* Deep expertise in Java-based engineering environments.
* Experience modernizing enterprise platforms and applications.
* Cloud platform experience, ideally within Azure environments.
* Ability to operate effectively at both strategic and technical levels.
* Experience working with globally distributed engineering teams.

Preferred Experience

* Payments, billing, checkout, or subscription platform experience.
* Consumer-facing commerce or transaction-based platforms.
* AI-driven platform modernization initiatives.
* Oracle database modernization or migration experience.
* AWS exposure.
* Familiarity with React.

Compensation

* Base Salary: $230,000 – $280,000
* Annual Bonus
* Equity: RSUs
* Total Compensation: Up to approximately $500,000

Location

This is a hybrid opportunity with a preference for candidates located in:

* Mountain View, California

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Senior Data Scientist
London (Hybrid, 2 days per week)

This is an opportunity to join a high-impact data science function at a business undergoing a major AI transformation. You will play a key role in shaping how advanced machine learning and personalisation are embedded into customer products, driving measurable improvements in engagement, wellbeing, and long-term outcomes. The role offers strong ownership, exposure to senior stakeholders, and the chance to deliver production-grade AI at scale.

The Company
They are a large, well-established organisation operating in a highly data-rich, customer-focused environment. With a strong emphasis on innovation, they are investing heavily in AI and machine learning to enhance their product offering and create more personalised user experiences. Their data science teams operate in a collaborative, cross-functional model, working closely with engineering, product, and business stakeholders. The organisation promotes a culture of continuous improvement, experimentation, and responsible AI adoption.

The Role

• Lead the end-to-end delivery of data science and machine learning solutions, from scoping through to deployment and monitoring
• Design and build production-ready ML systems, including recommender systems, segmentation models, and optimisation solutions
• Translate complex business challenges into scalable, data-driven solutions with measurable impact
• Own technical delivery within a pod structure, guiding and mentoring other data scientists
• Collaborate with data engineering, software engineering, and product teams to deliver robust, scalable platforms
• Drive best practices in model deployment, version control, CI/CD, and performance monitoring
• Engage senior stakeholders to influence decision-making and support broader AI adoption across the business
• Contribute to the development of new AI-driven initiatives, including early-stage generative AI use cases

Your Skills & Experience

• Strong commercial experience in machine learning and data science, including regression and classification techniques
• Advanced Python and SQL skills, with a focus on building and deploying production-ready solutions
• Proven track record of delivering end-to-end data science projects in a business environment
• Experience working in cross-functional teams and collaborating with technical and non-technical stakeholders
• Demonstrated ability to lead projects, mentor others, and operate effectively in ambiguous environments
• Familiarity with modern ML tooling, version control, and deployment practices
• Exposure to cloud environments or generative AI is beneficial but not essential

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Senior AI/ML Engineer – Foundation Models & Agentic AI
Life Sciences AI | Biotech / Therapeutics / Computational Biology

What You’ll Work On

• Develop and train proprietary foundation models on multi-omics data (genomics, transcriptomics, proteomics, metabolomics)
• Design novel algorithms to integrate and differentiate across omics modalities
• Own the full training pipeline: data ingestion, tokenization, pretraining, and evaluation
• Push the state of the art – we are building models that do not exist yet

Agentic AI for Life Sciences

• Build and deploy AI agents that assist researchers across therapeutic development, computational chemistry, and biology
• Design multi-agent architectures using LangChain, LangGraph, and custom orchestration layers
• Integrate agents with internal databases, experimental systems, and third-party scientific tools
• Develop agentic workflows for use cases in cosmetics R&D, drug discovery, and clinical analysis

Production ML Infrastructure

• Own model deployment, scaling, and serving infrastructure
• Optimize inference using NVIDIA TensorRT-LLM, Dynamo, Triton, and related tooling
• Partner with software engineering on integration into our broader platform
• Maintain reliability, performance, and observability across deployed models

What We’re Looking For

Required

• Strong hands-on ML/AI engineering experience – you write real code, not just direct others
• Deep proficiency in Python and PyTorch – this is non-negotiable
• Experience training, fine-tuning, and deploying foundation models from scratch or from pretrained checkpoints
• Familiarity with the Hugging Face ecosystem (Transformers, Datasets, PEFT, Accelerate)
• Experience with LangChain and/or LangGraph for agentic pipeline development
• Working knowledge of the NVIDIA stack: TensorRT-LLM, Triton Inference Server, Dynamo
• Comfort with large-scale distributed training tools: DeepSpeed, xFormers
• Strong understanding of state-of-the-art model architectures (transformers, SSMs, diffusion, etc.)
• Ability to collaborate across technical and non-technical teams – bio, chem, software, clinical
• Excellent communication skills – you can explain a training run to a chemist

Strongly Preferred

• Experience with omics data (any modality: genomic, proteomic, transcriptomic, metabolomic)
• Background in computational biology, computational chemistry, or bioinformatics
• Prior work in biotech, pharma, or life sciences AI (not required but a plus)
• Experience building or contributing to multi-agent systems in a production environment
• Track record of independent research or open-source contributions in ML

Technical Skills Summary

Core ML / Training

• PyTorch – primary framework
• DeepSpeed – distributed training and ZeRO optimization
• xFormers – memory-efficient attention and transformer components
• Hugging Face Transformers, PEFT, Accelerate
• Training and fine-tuning large language and multimodal models

Inference & Deployment

• NVIDIA TensorRT-LLM – high-performance LLM inference
• NVIDIA Dynamo – inference orchestration and scheduling
• Triton Inference Server – model serving and batching
• Model quantization, distillation, and latency optimization

Agentic & Orchestration

• LangChain / LangGraph – agent design and multi-agent orchestration
• Tool-use, RAG pipelines, and memory systems
• API and system integration across scientific data sources

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Senior Computer Vision Engineer (2D or 3D – Clinical AI)

About the Company

The mission is simple but ambitious: democratize access to high?quality cardiac care, especially in regions where cardiologists and advanced imaging equipment are scarce.

About the Role

This is a hands-on applied engineering position focused on building and deploying real clinical AI, not academic experiments. You will own production imaging models end?to?end, ensure reliability across diverse clinical settings, and work closely with clinical, regulatory, and deployment teams.

Profile A –

• Segmentation
• Localization
• Ultrasound/Echo image processing
• Signal and noise?robust imaging pipelines

Profile B – 3D Modeling

• Volumetric reconstruction
• 3D geometry and physics-informed modeling
• Computational representations of cardiac structures

Exceptional candidates may be considered for both tracks.

What You Will Own

Computer Vision Development

• Build production-grade CV models used in live cardiac workflows
• Develop 2D segmentation, 3D/4D reconstruction, and mathematical modeling systems
• Optimize models for low?latency clinical deployment
• Debug imaging pipelines across noisy, highly variable datasets

Production ML & Deployment

• Own pipelines from prototype ? production
• Support deployment engineers with real?world constraints
• Maintain model reliability across multiple international regions
• Monitor drift, performance degradation, and operational issues

What We’re Looking For

Required

• Strong experience in Computer Vision (2D and/or 3D)
• Production ML experience-beyond research or academic prototypes
• Background in biomedical or clinical imaging (ultrasound strongly preferred)
• Ability to debug, iterate, and deliver under pressure
• Experience working with deployment or ops engineering teams
• Comfort writing regulatory?oriented technical documentation
• Strong Python + PyTorch skills
• Startup mindset – bias for action, adaptability, ownership

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AI Engineer
San Francisco, California

Remote

$200,000 – $220,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As an AI Engineer, you will design and deliver applied AI systems (LLMs/CV/multimodal) that automate clinical variable abstraction and clinical note generation-with repeatable validation, robust documentation, and HITL feedback loops. Heavy emphasis on data engineering and backend rigor to make models usable and efficient.

Role Responsibilities

• Build models and pipelines across EMR/EHR, imaging, clinical reports
• Translate ambiguous clinical requirements into measurable ML objectives
• Define metrics, design experiments, estimate error; review peer work
• Deliver validated AI components for abstraction/note generation; meaningfully reduce manual QA workload via HITL; standardize documentation/testing; establish performant data manipulation patterns (e.g., PySpark, SQL/Postgres) that speed iteration.

Key Requirements

• Python
• Pytorch or Tensorflow
• Data engineering: PySpark, SQL, Postgres, query tuning, data modeling
• Cloud data platforms (e.g., Databricks, S3/Snowflake/Azure/GCP)
• Nice to have experience in oncology/biotech/health tech

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Clinical Data Scientist
San Francisco, California

Remote

$160,000 – $190,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As a Clinical Data Scientist, you’ll execute the last leg of the clinical data pipeline by transforming, cleaning, validating, and delivering high‑quality clinical datasets for pharma partners. Heavy collaboration with Clinical Ops, AI Engineering, and Data Delivery.

Role Responsibilities

• Transform raw, abstracted, and AI‑processed data into CDISC SDTM/ADaM datasets
• Program statistical outputs (tables, listings, figures) in SAS/R/Python
• Investigate data anomalies across multiple messy data inputs
• Define data dictionaries and standards before study kickoff
• Handle data in a HIPAA‑aligned manner

Key Requirements

• 2-5 years in clinical data science, stat programming, or clinical data management
• Pharma/Biotech experience
• SAS, R, Python, SQL
• Real‑world clinical data or oncology trials
• CDISC SDTM/ADaM

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Senior Machine Learning Engineer
Fully Remote, United States | $200,000 to $230,000 base plus equity and benefits

This is a high impact opportunity to shape how Vision Language Models are applied in real world, production grade systems. You will play a central role in building and scaling VLM driven intelligence that connects edge devices with cloud based reasoning, influencing both technical direction and product outcomes in a fast moving environment.

The Company
They are a technology led organisation building intelligent, connected solutions that blend advanced machine learning with real world operational workflows. Their platform is designed to turn complex visual data into actionable insights at scale. The team brings together expertise across machine learning, computer vision, embedded systems and data science, with a strong focus on building systems that perform reliably in production.

The Role

• Own the design and development of cloud based Vision Language Model pipelines used for large scale labelling and annotation
• Drive decisions on what visual signals, metadata and contextual information are captured from edge devices to maximise VLM performance
• Build and evaluate end to end inference systems, including prompt design, fine tuning strategies and model benchmarking
• Partner closely with embedded systems, computer vision and data science teams to close the loop between devices and cloud intelligence
• Stay at the forefront of the VLM landscape, assessing and integrating commercial and open source models as capabilities evolve

Your Skills and Experience

• Strong commercial experience as a machine learning engineer working with computer vision, LLMs or Vision Language Models
• Hands on experience evaluating, fine tuning or deploying VLMs in production environments
• Deep understanding of how edge constraints such as bandwidth, latency and compute influence model design
• Proficiency with Python, PyTorch and modern cloud based inference and evaluation tooling
• Practical expertise in prompt engineering and model evaluation, with a focus on measurable performance improvements
• Comfortable owning problems end to end and collaborating across hardware and software teams

What They Offer

• Competitive base salary of $200,000 to $230,000 plus equity
• Fully remote working across the United States
• Comprehensive benefits including medical, dental and vision cover
• Flexible paid time off and a strong culture of autonomy and trust
• The opportunity to be a technical leader in the application of Vision Language Models at scale

How to Apply
If you are excited by the challenge of building production grade VLM systems with real world impact, apply now to learn more about this opportunity.

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Senior Machine Learning Engineer / ML Scientist
Remote, United States
$160,000 to $210,000 base salary plus bonus and equity

This is an opportunity to join a high-impact machine learning team where your work directly influences real-time decisioning at scale. You will operate with a high level of ownership, designing and deploying models that solve complex problems in a production environment. The role blends scientific experimentation with strong engineering execution, offering the chance to shape both model performance and the systems that support it.

The Company

They are a fast-growing technology business operating at the intersection of machine learning and financial risk within e-commerce. Their platform enables large-scale, real-time decision-making across global transactions, helping customers optimise outcomes while reducing risk exposure.

The Role

* Design, build, and deploy machine learning models that operate in high-scale, real-time environments
* Own the full lifecycle of ML projects from experimentation through to production deployment and monitoring
* Develop advanced modelling approaches, including ensemble methods and performance optimisation techniques
* Build and improve offline evaluation frameworks to ensure robust and reliable model performance
* Work with large-scale distributed systems and datasets using tools such as Python, SQL, and Spark
* Collaborate cross-functionally with engineering, product, and risk teams to translate business challenges into ML solutions
* Contribute to a culture of experimentation, innovation, and continuous improvement within the ML function

Your Skills & Experience

* Strong commercial experience delivering machine learning solutions in production environments
* Deep understanding of machine learning theory, statistical modelling, and evaluation methodologies
* Proven ability to design and run experiments independently, from problem definition through to insight generation
* Experience working with large-scale distributed data processing systems, particularly Spark
* Strong programming skills in Python and SQL
* Experience taking models from research through to scalable deployment
* Academic background in a quantitative field such as Computer Science, Statistics, or similar is valued
* Experience in fraud, payments, or e-commerce is beneficial but not essential

What They Offer

* Competitive base salary between $160,000 and $210,000 depending on level and location
* Annual bonus and equity package
* Unlimited paid time off
* Retirement plan with employer contribution
* Comprehensive healthcare, dental, and vision coverage
* Paid parental leave and wellbeing support
* Learning and development budget
* Flexible remote working with minimal in-person requirements
* Clear progression opportunities within a growing machine learning organisation

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