To Apply for this Job Click Here

What You’ll Do

• Build and ship production-grade GenAI features (often 0→1)
• Own the end-user experience of AI-powered workflows
• Work closely with Product and Design to translate AI into intuitive UX
• Lead technical direction, mentor engineers, and set best practices
• Help define AI tooling, infrastructure standards, and evaluation approaches
• Balance fast iteration with scalability, reliability, and responsible AI

What We’re Looking For

• 7+ years of software engineering experience
• Staff-level mindset with proven technical leadership
• Strong frontend or frontend-leaning full-stack background
• 2-3+ years of hands-on GenAI experience
• Experience integrating LLMs into real products (not just demos)
• Strong product sense and user-first thinking
• Experience shipping features used by many users
• TypeScript experience preferred
• Cloud experience (Azure preferred; AWS/GCP acceptable)

Nice to Have

• B2C or consumer-facing product experience
• B2B experience with governance or data constraints
• Experience with chat-based UX, copilots, or assistants
• Familiarity with GenAI frameworks (e.g., LangChain)

Tech Stack

• TypeScript
• React, Node.js
• Azure (AWS/GCP acceptable)
• LLM APIs / GenAI tooling

To Apply for this Job Click Here

To Apply for this Job Click Here

What You’ll Do

• Own the end‑to‑end strategy and execution for public and private cloud platforms
• Lead a large, distributed organization (50-100+ engineers) across the US and India, including managers and senior technical leaders
• Unify currently siloed private and public cloud functions into a single, coherent platform
• Drive delivery of cloud infrastructure spanning:
• Kubernetes and container platforms
• Compute, GPU, and storage services
• Networking, identity, security, and access
• Infrastructure‑as‑Code and automation
• Provide direction and accountability to architects and senior engineers, ensuring decisions are made and executed
• Build a strong operating model that balances autonomy, reliability, cost control, and speed
• Establish trust and credibility within a deeply technical engineering culture
• Partner closely with leaders across technology, security, and the business to ensure alignment and outcomes

• Public and private cloud are no longer disconnected-they operate as one platform
• Strategy doesn’t stall at design; platforms are built, adopted, and running in production
• Teams are autonomous, accountable, and delivering reliably at scale
• Architects are aligned and decisively driven toward execution
• Cloud platforms are cost‑effective, resilient, secure, and easy for internal teams to consume

Required Experience

• 12+ years in cloud, infrastructure, or platform engineering roles
• 5+ years leading managers and senior technical leaders
• Proven ownership of both private and public cloud environments (this is non‑negotiable)
• Strong public cloud experience across at least two of: AWS, Azure, GCP
• Deep private cloud experience (VMware, Kubernetes‑led platforms, or equivalent)
• Strong Infrastructure‑as‑Code background (Terraform, Ansible, Python, or similar)
• Experience building self‑service internal platforms or IaaS products
• Solid grounding in networking, security, identity, and distributed systems
• Taking strategy from concept to delivery

Nice to Have

• Leadership experience with OpenShift or upstream Kubernetes
• Experience building GUI‑ or portal‑based private cloud platforms
• DevOps, SRE, or Internal Developer Platform (IDP) leadership experience
• Exposure to high‑performance compute, GPU workloads, or advanced analytics platforms

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead AI Engineer

$200,000

Location: Pittsburgh, PA (Onsite)

THE COMPANY

A high‑growth, mission‑driven technology organisation is expanding its advanced AI function. The team specialises in building intelligent autonomous systems designed to operate across complex workflows and high‑stakes environments. Engineers here work on cutting‑edge agentic technologies with significant ownership and impact.

THE ROLE

As the Lead AI Engineer, you’ll guide a specialised engineering team responsible for designing, building, and deploying next‑generation agentic AI systems. You will lead technical strategy, architecture decisions, and hands‑on development, while also mentoring engineers and driving best‑in‑class standards for performance, reliability, and scalability.

You’ll oversee the development of agents capable of long‑horizon planning, tool‑use, memory, and coordination across multi‑agent environments, ensuring they can operate effectively in real‑world mission‑critical settings.

KEY RESPONSIBILITIES

• Lead the design and development of agentic AI systems from conception through production
• Architect multi‑agent systems with planning, routing, memory, and complex tool‑use
• Build modular “skills” and components that plug into backend systems and data pipelines
• Establish evaluation frameworks, telemetry systems, and observability tools for agent behaviour
• Guide Agile processes, technical planning, and day‑to‑day engineering execution
• Partner with product and delivery teams to solve complex operational challenges
• Provide mentorship and technical leadership to engineers and data scientists

EXPERIENCE REQUIRED

• Several years of experience building and deploying ML or LLM‑powered systems in production
• Experience leading or mentoring engineering teams
• Demonstrated expertise in LLM integration and agentic system development
• Strong Python engineering skills
• Hands‑on experience with cloud infrastructure (AWS preferred)
• Familiarity with LLM algorithms, scaling patterns, and system reliability
• Ability to operate autonomously in high‑pace, ambiguous environments
• Comfortable with Git and modern engineering workflows

DESIRABLE EXPERIENCE

• Experience designing or deploying complex multi‑agent architectures
• Exposure to startup or high‑growth engineering cultures
• Experience with GenAI coding tools or best practices for agentic systems
• Eligibility to work in secure or sensitive environments

THE OFFER

• Ownership over next‑generation agentic AI strategy and architecture
• Opportunity to lead a high‑impact engineering team
• Work with cutting‑edge LLM and agentic technologies
• Fast‑paced environment with strong technical autonomy

To Apply for this Job Click Here

To Apply for this Job Click Here

Data Scientist (LLM)

Location: Chicago

Salary: Up to $170,000 + Benefits

An exciting opportunity has arisen for a Data Scientist to join a global SaaS organization that is transforming decision-making across a critical sector. With thousands of clients worldwide, this company is dedicated to delivering innovative solutions that drive measurable impact and operational efficiency.

The Role

The successful candidate will join a high-performing Analytics & Insights team, responsible for building predictive models and intelligent data pipelines that enable data-driven strategies. This position plays a key role in shaping product development and improving customer outcomes.

Key Responsibilities:

• Develop advanced statistical models and machine learning algorithms for predictive analytics and forecasting.
• Extract, clean, and transform complex datasets using SQL, Python, and modern ETL frameworks.
• Design and implement experiments to validate product impact and optimize outcomes.
• Collaborate with engineers, product managers, and domain experts to translate business challenges into data solutions.
• Implement monitoring and validation tools to ensure data quality and reliability.

What They’re Looking For

• Mid-level experience in data science or machine learning, ideally within SaaS or a data-driven industry.
• Proven track record of building and deploying end-to-end data solutions.
• Strong knowledge of statistical analysis, regression, time-series forecasting, clustering, and experimental design.
• Hands-on experience with SQL, Python (or R), and distributed data technologies (e.g., Spark, Hadoop, Kafka, or cloud platforms like AWS/GCP/Azure).
• Ability to troubleshoot and maintain scalable data workflows.
• A collaborative mindset and passion for using data to drive impact.

To Apply for this Job Click Here

To Apply for this Job Click Here

Principal Engineer, AI/ML

Location: Hybrid – Canada or U.S. (Toronto, Ann Arbor, Frisco, Eagan)

About the Opportunity

We’re partnering with the innovation lab of a global enterprise organization at the forefront of applying AI, machine learning, and data science to real-world professional workflows.

This group operates like a startup within a large-scale platform, building cutting-edge products that leverage LLMs, generative AI, and agentic systems to transform how users interact with complex information.

• AI-powered research and summarization
• Intelligent content and knowledge systems
• End-to-end automation of high-value professional workflows

This is a rare opportunity to work on AI-native products at scale, with meaningful real-world impact.

Role Overview

As a Principal Engineer, AI, you will lead the design and delivery of next-generation AI systems, driving technical strategy and building scalable, production-grade GenAI applications.

You’ll operate at the intersection of:

• Architecture
• Hands-on engineering
• Cross-functional leadership

What You’ll Do

• Define and drive technical strategy for large-scale AI initiatives
• Architect and build LLM-powered applications and agentic systems
• Lead development of AI-native features for content and knowledge platforms
• Design scalable systems leveraging RAG, prompt engineering, and fine-tuning
• Integrate GenAI into user-facing applications and workflows
• Mentor and guide senior engineers and technical leaders globally
• Partner with product and business teams to translate requirements into technical solutions
• Own delivery of complex, high-impact engineering initiatives

Core Tech Areas

• AI/ML: LLMs, Generative AI, RAG, Agentic Systems
• Languages: Python, Java, TypeScript (varies by team)
• Cloud: AWS, Azure, or GCP
• Frameworks: LangChain, LLM tooling, modern AI dev frameworks
• Practices: DevOps, CI/CD, scalable distributed systems

What They’re Looking For

• 10+ years of hands-on software engineering experience
• Proven experience building scalable AI / ML / GenAI systems in production
• Strong understanding of:
• LLMs and generative AI
• RAG architectures
• Prompt engineering and fine-tuning
• Agent-based / agentic systems
• Experience working in cloud environments (AWS, Azure, or GCP)
• Background in enterprise SaaS or large-scale platforms
• Ability to operate in ambiguous, fast-moving environments
• Strong communication skills and ability to influence across teams
• Experience mentoring engineers and driving engineering best practices

Nice to Have

• Experience building AI systems for content, knowledge, or domain-specific workflows (e.g., legal, compliance, research)
• Familiarity with AI governance, evaluation, and responsible AI practices
• Advanced degree in Computer Science, Engineering, or related field

Why This Role

• Work on cutting-edge GenAI systems with real-world impact
• Combine startup velocity with enterprise scale and resources
• High visibility role with influence across product and engineering strategy
• Opportunity to shape AI-native platforms from the ground up

Ideal Candidate

• Deeply technical AI/ML engineer with architectural mindset
• Comfortable owning systems from design → build → scale
• Passionate about LLMs, agentic systems, and applied AI
• Thrives in environments requiring ownership, autonomy, and leadership

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Scientist – Applied Modeling

REMOTE – US

$170,000-$200,000 + Equity

We’re recruiting for a high‑growth AI technology company whose products power audience modeling, bid optimisation, contextual targeting, and measurement for major brands. They are looking for a Senior Data Scientist to own model performance in production, working across both experimentation and real‑world optimisation.

This is a hands‑on applied role, deeply connected to product and engineering teams.

What you’ll be doing

• Building, configuring, and improving models for audience scoring, lookalikes, optimisation & measurement
• Running diagnostics, drift detection, lift analysis, and performance tuning
• Developing pipelines and feature workflows in Python, SQL, and PySpark
• Supporting experimentation frameworks and producing actionable insights
• Collaborating with product, engineering, and client‑facing teams
• Feeding field learnings back into the modeling lifecycle

What they’re looking for

• 5+ years in Data Science / ML
• Strong Python, PySpark, SQL, and ML frameworks (PyTorch/sklearn)
• Experience owning models in production, not just research
• Strong communication and ability to translate model outputs into business decisions
• Experience with NLP or contextual models is a strong plus

Why this role

• Models directly tied to real‑world performance
• High variety across modeling, experimentation, and production ownership
• Opportunity to shape the next generation of applied ML products
• Strong compensation + equity package

HOW TO APPLY

If you want a high‑impact DS role where your models drive real‑world outcomes, we’d love to hear from you.

To Apply for this Job Click Here

To Apply for this Job Click Here

The Company
We’re partnered with a fast-growing, product-led SaaS company where data plays a central role in product decision-making. The data team works closely with senior leadership and is continuing to scale.

The Role
This is a Staff-level individual contributor role within the Product Analytics team, focused on owning and scaling the company’s experimentation framework.

The organization is continuing to build its experimentation maturity, and this hire will play a key role in strengthening both the technical implementation and adoption of experimentation across the business.

You will act as a technical anchor for the team, ensuring robust statistical practices while working closely with stakeholders to support data-informed product decisions.

Key Responsibilities

• Own and scale the experimentation roadmap across product teams
• Design and implement robust experimentation frameworks (e.g., Bayesian methods, sequential testing)
• Apply causal inference to user behavior, feature adoption, retention, and churn
• Partner with product and engineering teams to ensure experiments are correctly designed and implemented
• Provide guidance to team members on advanced statistical methods
• Work with stakeholders to support adoption of experimentation best practices
• Evaluate and support implementation of experimentation tooling

Requirements

• 6+ years of experience in Data Science or Product Analytics
• Strong experience with experimentation (A/B testing, Bayesian methods, or similar approaches)
• Solid understanding of causal inference
• Experience working in SaaS product environments
• Ability to work with a high level of ownership and collaborate effectively with stakeholders

Technical Skills

• Python
• SQL
• Experience working in shared code environments (e.g., GitHub)

Nice to Have

• Experience evaluating or implementing experimentation platforms
• Exposure to modern AI-assisted tools (e.g., Cursor, Claude Code)

Additional Information

• Opportunity to contribute to the development of experimentation practices within a growing product organization
• High-visibility role with direct impact on product decision-making
• Fully remote within the US, aligned to EST working hours

Eligibility
Applicants must have the right to work in the United States. Sponsorship is not available.

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Machine Learning Engineer, LLM (Applied AI/NLP)

Location: New York (Hybrid)

Compensation: $180K-$220K base + equity + bonus

About the Company

Join a fast-growing AI startup transforming how development teams build and scale modern applications. Their intelligent platform uses LLMs to automate coding tasks, streamline workflows, and boost developer productivity.

The Role

Lead the design and deployment of advanced NLP/LLM solutions that directly impact engineering workflows code generation, documentation, and review automation. Collaborate with senior leadership to take models from research to production.

Key Responsibilities

• Build and fine-tune LLMs for developer-focused use cases
• Optimize models using prompt engineering, RAG, and inference techniques
• Collaborate across teams to align AI capabilities with product goals
• Mentor junior ML engineers and contribute to internal innovation

What You’ll Bring

• 2-8 years in applied NLP/LLM development
• Strong Python and ML stack (PyTorch, HuggingFace, etc.)
• Experience with large code/text datasets and transformer models
• Advanced degree in CS, AI, or NLP (PhD preferred)
• Bonus: Publications in top-tier ML/NLP conferences

Why Join?

• Competitive pay + equity + bonus
• Direct impact on product innovation and IP
• Full benefits: health, vision, dental, 401(k), generous PTO

How to Apply

To explore this opportunity, please submit your resume to Luc Simpson-Kent using the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Machine Learning Engineer

Location: New York (Hybrid)

Compensation: $180,000 – $250,000 base salary + Equity

About the Company

We’re partnered with a cutting-edge software company that’s redefining how development teams build, maintain, and scale modern applications. As engineering workflows grow increasingly complex, their intelligent platform empowers teams by deploying AI agents that automate repetitive development tasks, streamline workflows, and enhance productivity. These AI-driven systems are already transforming the software development lifecycle in dynamic environments-and the company is now scaling rapidly to meet market demand.

The Role

As an Applied AI/NLP Scientist, you’ll play a key role in designing and deploying advanced NLP and LLM-based solutions that accelerate and enhance software engineering workflows. Working directly with senior technical leadership, you’ll drive projects from early-stage research to production-ready implementations, with real impact on the development process.

Key Responsibilities

• AI Model Innovation: Architect and implement domain-specific LLM/NLP models tailored to the needs of software engineering use cases-code generation, documentation automation, code review assistance, and more.
• Research to Production: Lead end-to-end development of NLP/LLM solutions, from proof-of-concept to scalable production systems.
• Model Optimization: Improve model efficiency and output through fine-tuning, prompt engineering, RAG (retrieval-augmented generation), and inference techniques.
• Cross-Functional Collaboration: Work alongside product managers, developers, and leadership to ensure AI capabilities align with platform strategy and user needs.
• Thought Leadership: Help shape best practices around applied NLP/LLM development, contribute to internal innovation, and author papers or patents where applicable.
• Mentorship: Provide guidance and mentorship to junior ML researchers and engineers.

Your Skills and Experience

We’re looking for a hands-on NLP expert with a passion for building tools that empower developers:

• 2-8 years of experience in applied NLP or LLM-focused system development.
• Proven track record building and deploying NLP/LLM solutions in production.
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace, spaCy).
• Experience working with large, unstructured code and text datasets.
• Background in applied research with an ability to bring experimental models into real-world systems.
• Deep understanding of transformer-based architectures, prompt tuning, fine-tuning, and retrieval-augmented methods.
• Strong communication skills and comfort working in fast-paced, ownership-driven environments.
• Advanced degree (PhD or Master’s) in Computer Science, AI, NLP, or a related field (PhD preferred).
• Bonus: Publications in top-tier AI/ML/NLP venues (e.g., NeurIPS, ACL, ICLR, EMNLP).

The Benefits

• Competitive Pay: $180,000 – $250,000 base + performance bonus + equity
• Innovation Ownership: Contribute directly to product innovation and IP
• Comprehensive Benefits: Health, dental, vision, 401(k), generous PTO, and more

How to Apply

To explore this opportunity, please submit your resume to Luc Simpson-Kent using the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Principal Machine Learning Engineer – ML Platform

REMOTE – US

$180,000-$230,000 + Equity

We’re partnered with a scaling AI‑driven technology company building large‑scale, production‑grade ML systems used in real‑time decisioning. They’re seeking a Senior Machine Learning Engineer who loves production ML over research, with an emphasis on distributed compute, reliability, and end‑to‑end ownership.

This is a role for someone who enjoys shaping platform architecture while still being hands‑on.

What you’ll be doing

• Designing, training, and deploying high‑scale ML models used in live systems
• Building distributed training pipelines (PyTorch, Ray)
• Owning the ML lifecycle across feature engineering, training, evaluation, inference, monitoring
• Improving ML reliability, observability, and reproducibility
• Working closely with engineering, SRE, and product to shape platform direction
• Contributing to ML architecture standards, CI/CD, and testing frameworks

What they’re looking for

• Strong experience delivering production ML systems end‑to‑end
• Expertise with Python, PyTorch, distributed compute (Ray, Spark)
• Background in large‑scale data processing and MLOps tooling
• Ability to diagnose production issues and drive architectural improvements
• Experience with event‑driven ML and model deployment frameworks is a plus

Why this role

• High ownership of ML platform direction
• Complex, real‑world ML workloads at meaningful scale
• Opportunity to improve and evolve existing infrastructure
• Equity + strong compensation package

HOW TO APPLY

If you’re passionate about building robust, scalable ML systems that drive real business impact, apply now.

To Apply for this Job Click Here