Our client, an innovator in the financial services industry, is hiring a Staff Machine Learning Engineer to join their team remotely. The successful candidate will leverage their expertise in data science and ML operations to enhance model accuracy while optimizing infrastructure for both scalability and cost efficiency.


Responsibilities

• Enhance their pricing model to boost accuracy for high-value cards while minimizing infrastructure costs.
• Refine our underwriting model to optimize cash advance disbursements while keeping risk and default rates in check.
• Own the full ML lifecycle, from model training and feature engineering to deployment and monitoring.
• Work closely with pricing experts to gain deep domain knowledge of the trading card market and drive model improvements.
• Plan and run experiments and back tests to identify and validate features that strengthen predictive performance.
• Manage AWS infrastructure and develop code for our pricing API to ensure scalable, low-latency model delivery.

Skillset

• Minimum of 10 years of engineering experience, including at least four years focused on machine learning.
• Deep expertise in Python, with hands-on experience in libraries such as scikit-learn, XGBoost and pandas.
• Strong ML Ops and infrastructure background, with experience deploying models on AWS using ECS and Docker.
• Skilled in data orchestration and workflow management using Airflow for model training and batch processing.
• Demonstrated success improving model accuracy through feature engineering and experimentation.
• Experience with Random Forest, ensemble methods, or pricing/underwriting models in marketplace or fintech environments.

Benefits

• Salary: Circa. $250k.
• Equity.
• Remote working.
• 401(k) retirement benefits.
• Competitive healthcare package.

Our client, an innovator in the healthcare industry, is hiring a hands-on Tech Lead Manager (Machine Learning) to join their team in Utah. The successful candidate will lead the development of the Personalization Engine, combining hands-on machine learning engineering with team leadership to build and scale production ML systems that deliver real-world impact.


Responsibilities

• Take ownership of the machine learning system that powers the organization’s Personalization Engine.

• Lead the end-to-end ML lifecycle, including model development, deployment, monitoring and optimization.

• Ensure the platform remains reliable and scalable across millions of healthcare transactions.

• Build advanced ML solutions such as ensemble models, reinforcement learning approaches and multi-armed bandit systems.

• Architect and maintain high-performance MLOps infrastructure, including feature stores, data pipelines and monitoring systems.

• Strengthen feedback loops so models continuously learn and improve based on real patient behaviour.

• Lead, manage and mentor a team of machine learning engineers.

• Carry out thorough code and system design reviews to uphold strong technical standards.

• Promote a culture focused on experimentation, continuous learning and meaningful impact.

• Partner closely with product and design teams to translate complex patient journey challenges into ML-powered solutions.

Skillset

• At least 6 years of experience designing and deploying machine learning systems in production environments at scale.

• Proven experience building personalisation or recommendation engines for consumer-facing products (e.g. fintech, e-commerce).

• Strong programming capabilities in Python and SQL.

• Minimum of 2 years’ experience leading teams, managing engineers or operating as a technical ML lead.

• Hands-on experience across the entire ML lifecycle, including data pipelines, model development and MLOps.

• Ability to translate business challenges into practical machine learning solutions.

• Experience incorporating Generative AI into personalisation platforms or features is a bonus.

• Broader product engineering leadership experience beyond ML-focused systems.

Benefits

• Salary: $195,000 - $245,000 DOE.

• Equity.

• Flexible and Remote working options.

• Health benefits.

• 401(k) with 100% match up to 3%

Our client, a fast-growing healthcare organization, are hiring a Machine Learning Engineer to join the team in New York or San Francisco. The successful candidate will play a key role in shaping the future of conversational AI by driving meaningful improvements in patient outcomes and transforming the way healthcare systems engage and communicate.


Responsibilities

• Develop and implement machine learning models tailored for SMS and voice-enabled conversational AI.

• Create scalable pipelines to support data ingestion, model training and real-time deployment.

• Fine-tune large language models using healthcare-focused datasets to enhance accuracy and relevance.

• Collaborate with full-stack engineering teams to seamlessly integrate AI capabilities into core product experiences.

• Lead the full lifecycle of model deployment, including monitoring, troubleshooting and iterative optimization.

• Continuously explore emerging AI/ML technologies and healthcare innovations to keep their solutions cutting-edge.

 

Skillset

• At least 4 years of experience in AI/ML engineering, with a strong focus on NLP, large language models and conversational AI.

• Proven track record of deploying ML models into production, preferably within healthcare or other regulated industries.

• Proficient in Python and experienced with ML frameworks such as TensorFlow and PyTorch.

• Strong skills in fine-tuning LLMs, prompt engineering and integrating models into real-world applications.

• Comfortable working with cloud platforms (e.g. AWS, Azure, GCP) and knowledgeable in MLOps practices for scalable deployments.

• Experience with voice and speech-based technologies, including recognition and generation.

• Hands-on background in designing and implementing conversational AI solutions.

• Exceptional analytical and communication abilities.

• Familiarity with HIPAA compliance and handling of sensitive healthcare data is a bonus.

Benefits

• Competitive Salary.

• Equity.

• Remote working.

• Comprehensive healthcare package.

Our client, an AI-driven organization in the Fintech industry, are hiring a Staff Machine Learning Engineer to join the team in Colorado. The successful candidate will will focus on building end-to-end generative AI products leveraging your deep expertise in large language models, fine-tuning techniques and reinforcement learning.


Responsibilities

• Design and build multi-agent systems that automate tasks and streamline workflows, delivering measurable operational impact.

• Develop AI co-pilots for advisors and other user personas, supporting workflows across prospecting, conversion, onboarding and client servicing.

• Create purpose-built, low-latency models for complex, multi-turn financial services interactions.

• Enable AI-driven optimisation and navigation of legacy platforms using computer-use and automation models.

• Design, fine-tune, and deploy open-source and proprietary LLMs for use cases including Q&A, summarisation, reasoning and planning.

• Build advanced Retrieval-Augmented Generation (RAG) pipelines, incorporating query rewriting, embedding fine-tuning, hybrid search, re-ranking and knowledge graphs.

• Apply reinforcement learning techniques, including RL fine-tuning methods such as PPO, DPO, and GRPO, to continuously improve model performance.

• Deploy models to production, ensuring high performance, reliability, scalability and low latency.

Skillset

• At least 5 years of experience in applied AI/ML engineering.

• Demonstrated success delivering production-grade generative AI products with large language models at their core.

• Hands-on experience with LLM fine-tuning techniques (e.g. LoRA), inference frameworks (e.g. vLLM) and advanced Retrieval-Augmented Generation (RAG) architectures.

• Strong practical expertise in reinforcement learning fine-tuning methods and supporting tooling.

• Previous experience working in an early-stage startup is a plus.

Benefits

• Salary: $170k - $220k DOE

Our client, a FinTech innovator, are hiring a Staff Machine Learning Engineer with expertise in Large Language Models (LLMs) to join the team remotely. The successful candidate will be responsible for building Generative AI and LLMs solutions in a in a fast paced environment that will help transform financial advice delivery.


Responsibilities

• Lead the development and customization of large language models tailored for financial use cases.

• Apply cutting-edge tuning methodologies to enhance performance across conversational AI, content generation and strategic reasoning tasks.

• Create intelligent retrieval systems that combine multiple search approaches, semantic understanding and ranking mechanisms to deliver contextually relevant information at scale.

• Engineer autonomous AI systems capable of independent decision-making, integrating feedback loops and adaptive learning techniques to continuously enhance agent capabilities.

• Establish comprehensive testing and monitoring frameworks while overseeing production deployments that maintain high-performance standards under real-world conditions.

• Work closely with cross-functional teams to transform AI research into market-ready features that solve genuine business challenges.

Skillset

• Minimum 5 years of professional experience applying machine learning in commercial settings post-graduation.

• Must have at least 2 years’ experience working with LLMs and finetuning like QLORA / LORA and building RAG systems.

• Demonstrable success delivering end to end ML /AI products where generative AI drives core functionality, with particular emphasis on systems that exhibit autonomous behavior patterns.

Benefits

• Salary: $190,000 - $225,000 .

• Equity.

• Comprehensive health/dental/vision coverage.

• Retirement plans.

If interested hit apply below or reach out to me at joseph.mcdermott@alldus.com