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

Our client, an innovator in the eCommerce industry, is hiring a Lead Machine Learning Engineer to join their New York team remotely. The successful candidate will play a pivotal role in shaping the future of their marketplace by developing intelligent, data-driven products that enhance user experience and fuel business growth. This includes optimising search and ranking, building impactful recommendation models and developing scalable systems that serve millions of users.


Responsibilities

• Lead the design, development and deployment of scalable machine learning models across key domains such as search relevance, advertising, pricing and recommendations.

• Architect and implement robust, production-ready pipelines and REST APIs to deliver models at scale.

• Partner closely with product managers, engineers and cross-functional stakeholders to translate business requirements into effective technical solutions.

• Explore, prototype and assess new algorithms and emerging technologies to drive continuous innovation.

• Take full ownership of machine learning initiatives, from ideation and data analysis through to deployment, monitoring and ongoing optimization.

Skillset

• At least 5 years of hands-on experience developing and deploying machine learning models in production environments.

• Deep knowledge of core ML techniques, including classification, regression, ranking and recommendation systems.

• Proficiency in Python and modern ML frameworks such as Scikit-learn, TensorFlow or PyTorch.

• Strong software engineering fundamentals, with experience building production-grade services and REST APIs.

• Practical experience working with cloud platforms such as AWS, GCP or Azure.

• Exposure to Large Language Models (LLMs) and their use in search, recommendations, or related applications is a big plus.

• Familiarity with MLOps tools and practices, including platforms like MLflow or Kubeflow.

• Experience working within e-commerce or online marketplace environments is a bonus.

Benefits

• Salary:  $160,000–$200,000 DOE

• Equity.

• Comprehensive benefits package.

• Remote working options.

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 exciting Series B FinTech Startup, is hiring a Staff Machine Learning Engineer to join the team remotely. The successful candidate will design and deploy advanced machine learning models to help build interpretable, high-performing and scalable solutions leveraging data from AWS and Snowflake environments to drive impactful, data-informed decisions.


Responsibilities

• Designing, developing and deploying machine learning models to support predictive analytics across key fintech applications.

• Collaborating closely with cross-functional teams, including Data, Engineering and Product, to deliver integrated, data-driven solutions.

• Ensuring high model performance and reliability through robust data pipelines and scalable infrastructure.

• Converting model outputs into actionable insights that drive business strategy and financial inclusion outcomes.

• Mentoring and supporting fellow team members to promote a culture of technical excellence and collaboration.

• Championing best practices in MLOps, data governance and regulatory compliance across the ML lifecycle.

Skillset

• PhD or Master’s degree in Computer Science, Mathematics, Statistics or similar.

• 10+ years of relevant experience in applying AI/ML techniques within the financial services or fintech sectors.

• Extensive experience developing and deploying machine learning models for tasks such as classification, regression and forecasting.

• Strong programming proficiency in Python and SQL.

• Hands-on experience with AWS, particularly SageMaker and Bedrock, for model training, deployment and fine-tuning.

• Familiarity with model lifecycle tools like MLflow, SageMaker Model Registry or similar platforms.

• Practical experience using PyTorch, Scikit-learn and Generative AI models.

• Knowledge of Large Language Models (LLMs) and frameworks such as Hugging Face, LangChain or Mirascope.

• Solid understanding of cloud-based data architecture, including Snowflake, Amazon S3 and PostgreSQL.

• Background working in FinTech, PropTech or startup environments is a bonus.

Benefits

• Salary: $200,000 - $235,000.

• Equity.

• Remote working.

• Comprehensive health, dental, and vision insurance.

• 401(k).

Our client, a leading Fintech company, are hiring a Staff Machine Learning Engineer to join their Applied AI team remotely. The successful candidate will be responsible for developing and deploying AI-powered multi-agent systems, human-in-the-loop co-pilots, specialized financial models and seamless legacy system integrations to automate processes, improve workflows and optimize existing financial technologies.


Responsibilities

• Design and fine-tune both open source and proprietary large language models (LLMs) for tasks including summarization, reasoning, planning and question answering.
• Build and enhance advanced Retrieval Augmented Generation (RAG) pipelines featuring embedding fine-tuning, hybrid search, reranking and knowledge graph integration.
• Develop autonomous AI agent workflows that support proactive and adaptive decision-making.
• Utilize reinforcement learning methods (such as PPO, DPO, GRPO) to continuously improve model performance.
• Create evaluation frameworks and define metrics to rigorously assess model effectiveness.
• Deploy AI models into production environments with a focus on low latency, reliability and scalability.
• Work closely with product and engineering teams to deliver comprehensive AI-powered financial solutions.

Skillset

• Master’s or Bachelor’s degree with at least 5 years of professional experience in applied AI/ML engineering.
• Demonstrated success in delivering generative AI products utilizing LLMs and autonomous agent workflows.
• Practical expertise with LLM fine-tuning methods (such as LoRA), inference frameworks (including vLLM) and sophisticated RAG pipelines.
• In-depth understanding of reinforcement learning fine-tuning techniques and associated frameworks.
• Early-stage startup experience is an advantage.

Benefits

• Salary: $190k - $225k DOE.
• Remote working.
• Comprehensive health, dental and vision coverage.
• Retirement benefits.

Our client, an exciting AI-driven company, are hiring a Machine Learning Engineer to join the team in Seattle, Washington or Palo Alto, California. The successful candidate will be instrumental in building and scaling the infrastructure behind the company’s open AI platform, leveraging strong platform engineering skills and a solid machine learning background to support everything from training workflows to production deployment.


Responsibilities

• Develop and sustain reliable systems for training, deploying and scaling AI models.
• Build and enhance workflows for data preparation, model training, evaluation and deployment.
• Identify and resolve performance bottlenecks to ensure smooth operation for thousands of users and contributors.
• Automate infrastructure provisioning, deployment and monitoring following DevOps best practices.
• Collaborate closely with researchers and developers, both within the company and across our open-source community.
• Contribute to the development and direction of their open-source platform and foundational AI models.

Skillset

• Extensive experience in infrastructure engineering, DevOps or cloud-native environments.
• Deep understanding of machine learning principles and practical experience with end-to-end ML workflows.
• Proficient in Python and skilled in best practices for software development.
• Practical knowledge of cloud platforms such as AWS, Google Cloud or Azure.
• Experience with distributed computing and designing scalable systems.
• Enthusiasm for open-source development and active participation in community-driven projects.

Benefits

• Salary: $100K - $220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.