Machine Learning Engineer Jobs

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 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

Staff Machine Learning Engineer
Location: Remote

Are you tired of being kept in a restricted creative box with limited autonomy to push boundaries and ideas to solve problems with ML? 

Or not seeing your work directly impact the companies mission? 

If so , my HealthTech client is looking for a Staff ML Engineer who will love being in an autonomous environment where you will be given a problem area but full autonomy to be creative, push new ideas and build the ML solutions you feel is best. 

You'll join a smart and curious team who like to be challenged working on areas like Recommender Systems, LLMs & NLP, Timeseries and MLOps.

You'll achieve success here by combining your technical ML/AI end-to-end building skills with high positive energy and clear articulate communication skills. 

What else is in it for you? 

• Base Salary from 210-260k 
• Equity/Stocks

What do you need to be successful? 

• Are a technical leader who can work and manage their own projects and solutions with full autonomy. Like a Staff/ Principal ML Engineer / Scientist
• You can clearly articulate your thoughts and write and communicate them clearly.
• Build ML/AI solutions end to end in the ML Lifecycle from research to production
• Comfortable with being challenged and taking feedback to build better solutions with the right outcomes
• Can move with speed and intent and comfortable with life building a startup/scaleup

Interested? Click the apply or For more info reach out at anthonyh@alldus.com

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, a well-funded AI startup, is hiring a Full-Stack Engineer with strong Machine Learning expertise to join their team in New York. The successful candidate will help define the product, architecture and culture from the ground up, from owning core systems, driving key technical decisions without bureaucracy and deploying your work into enterprise AI environments within weeks.


Responsibilities

• Take ownership of projects end-to-end, from backend APIs to frontend dashboards to LLM integrations.

• Design, build and deploy full-stack features that power their AI agent platform.

• Create and maintain evaluation pipelines for LLMs, including RAG and agentic workflows.

• Build monitoring and analytics tools to measure reliability, accuracy and trustworthiness.

• Partner with researchers to turn cutting-edge evaluation and correction techniques into production-ready features.

• Deploy secure, scalable services on AWS/GCP with Docker and Kubernetes.

Skillset

• At least 5 years of experience building and scaling production-ready backend and frontend systems.

• Strong skills in Python and TypeScript/React, plus proficiency in at least one strongly typed backend language (Go, Java, or C++).

• Hands-on experience with AWS or GCP, Docker/Kubernetes, and modern CI/CD pipelines.

• Familiarity with LLM tooling (e.g. LangChain, Pinecone, vector databases) is a strong plus.

• Comfortable working across the stack, from system architecture to debugging to UI polish.

• Experience with RAG or agentic evaluations or deploying AI agents in production is a plus.

• Prior experience working in a fast-paced startup is a bonus.

Benefits

• Salary:  $150K - $170K

• Equity.

• 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, a cutting-edge AI company revolutionizing software development, is hiring a Senior Software Engineer, AI Platform to join their team in New York. The successful candidate will contribute to designing and building the next-generation real-time layer for executing, deploying, governing and auditing AI applications, workflows and agents.


Responsibilities

• Develop, implement and fine-tune enterprise-level AI models and reliable production workflows.
• Create and maintain a real-time distributed execution engine that supports AI applications, agents and workflows.
• Design scalable and resilient systems that enable multi-tenant and hybrid cloud deployments, featuring secure APIs and a versatile integrations platform.
• Work closely with customers and design partners to collect feedback, validate approaches and guide product development.
• Collaborate with the product team to shape the roadmap and keep pace with the latest advancements in AI infrastructure.

Skillset

• At least 5 years of experience deploying and managing production applications in cloud environments.
• Extensive knowledge of containers, virtual machines, caches, task queues, networking and operating systems.
• Proven experience in building and running production AI systems.
• Familiarity with AI inference methodologies.
• Proficient with machine learning frameworks such as PyTorch and TensorFlow.
• Strong product intuition with a commitment to delivering smooth and intuitive user experiences.
• Strategic thinker who can anticipate market demands and develop effective technical solutions.
• Startup mindset - quick to act, comfortable with uncertainty, and passionate about turning ideas into delivered products.

Benefits

• Salary: $170K - $210k
• Equity
• Remote working within the U.S.