data engineer

software engineer

data engineer ii

data scientist

ai engineer

machine learning engineer

Meltwater

<div>Description 
 
Meltwater, a pioneer of media intelligence and now Outside Insight, gives businesses the information advantage they need to stay ahead. More than 30,000 companies have used Meltwater&rsquo;s media intelligence to stay on top of billions of online conversations and extract relevant insights to strategically manage their brands. Meltwater is dedicated to personal, global service built on the local expertise of 55 offices across six continents. Meltwater is also committed to fostering the data science ecosystem through MEST, a pan-African entrepreneurial program and incubator, and Shack15, a global data science community.
 
 
Our AI team is young, ambitious and focused on innovation.
 
 
With Meltwater, we are more than 2000 people across the globe, so there is a lot going on. We believe in diversity and inclusion, and building teams with a wide variety of backgrounds and perspectives. This approach not only raises the quality of our products for our customers, but makes collaboration along the way much more fun. 
 
Read our underthehood blog to see which problems our engineers are solving. 
 
Meltwater&rsquo;s Consumer Intelligence AI Team is looking for a Machine Learning Engineer to help improve the multimodal semantic layer of MIRA, our AI assistant, while also developing innovative new features that power the next generation of applied generative AI in the Consumer Intelligence industry. This includes building agentic capabilities that allow MIRA to reason across data sources, orchestrate multi-agent/multi-step workflows, and generate complex, use-case driven reports for customers. 
 
We are looking for someone with a creative, proactive, collaborative, and innovation focused mindset. You will work alongside a team of passionate machine learning engineers driven by enthusiasm for adopting new technologies and excitement about making the difference for customers using applied AI. 
 
As a Machine Learning Engineer at Meltwater, you will own machine learning powered features from idea to production, working on systems that operate at massive scale. You should be comfortable with experimentation, collaboration, and real-world impact. 
 
What we're looking for: 
 
This role is ideal for candidates with a strong foundation in machine learning, data science, or applied research who enjoy experimentation and model-driven problem solving and who want to translate their work into real-world, production systems at scale. You are excited to grow your software engineering and production skills over time, while bringing strong foundations in experimentation, modeling, evaluation, and applied machine learning. 
 
Our team is organized over 3 objectives : innovation, research and production. 
 
Innovation: We leverage our AI expertise to constantly imagine new business oriented features to enhance our products. 
 
Research: To implement our algorithms, we need to stay up-to-date to the latest breakthroughs over the Machine Learning world as well as the latest frameworks. 
 
Production: We make a point of designing and developing our algorithms with production-grade best practices. Scalability is our goal. The models and systems that we develop are running over billions of documents (text or image) per day. 
 
Responsibilities: 
<ul><li>
Drive the development of industrial ML projects from ideation to deployment, contributing across early prototyping, research, evaluation, and progressively to production, scalability, and monitoring with support from the team.</li><li>
Collaborate closely with product teams in their domains, building domain expertise, and leveraging ML to solve critical business problems</li><li>
Keep up-to-date with the latest advancements in machine learning to stay current on emerging techniques to solve novel problems</li><li>
Design, run, and iterate on machine learning experiments to improve model quality and product impact</li><li>
Develop features, online and offline evaluation metrics, and validation strategies for large-scale ML systems</li><li>
Analyze model errors and failure modes to understand limitations, biases, and opportunities for improvement.</li></ul> 
 What You'll Do: 
<ul><li>
Drive the development of new industrial level projects from ideation to deployment. This includes deep expertise in areas such as early ideation &amp; prototyping, research, infrastructure, scalability, monitoring, and evaluation of AI systems.</li><li>
Collaborate closely with product teams in their domains, building domain expertise, and leveraging ML to solve critical business problems</li><li>
Keep up-to-date with the latest advancements in machine learning to stay current on emerging techniques to solve novel problems</li><li>
You&rsquo;ll write efficient, well-tested and design code, build clean systems to empower MIRA with new advanced generative AI capabilities</li><li>
Demonstrable experience with the full lifecycle of machine learning models - from development to deployment and monitoring</li><li>
Experience building industry-scale user-facing ML/AI/Agentic applications</li><li>
Experience with MLOps and DevOps principles and technologies (e.g. CI/CD, Terraform, Containerization, Kubernetes)</li><li>
Experience with Information Retrieval systems in a production environment (Elasticsearch, Quickwit, Vespa, &hellip;) is a plus</li></ul> 

What You'll Bring: 
<ul><li>
2 - 5 years experience applying machine learning techniques through academic, professional, or personal projects, ideally with exposure to experimentation, modeling, or applied research.</li><li>
Solid foundation in machine learning concepts such as feature engineering, model selection, training, validation, and error analysis</li><li>
Ability to write clear, well-structured code, with motivation to grow software engineering skills and contribute to production ML systems</li><li>
Experience reasoning about metrics, tradeoffs, experiments, and uncertainty in applied ML problems</li><li>
You are comfortable learning new tools, concepts, or techniques as needed, and enjoy expanding beyond your initial area of strength.</li><li>
Advanced knowledge in a least one programming language (Python or other e.g. Rust, Scala, Java)</li><li>
Passion for AI (in particular Generative AI), with a constant drive to stay updated and ahead of the curve</li><li>
You are a team-player, self-learner and autonomous</li><li>
MS, PhD, or equivalent practical experience in machine learning, data science, or a related technical field</li></ul> 

What We Offer: 
<ul><li>
You will work with a team of passionate people who are always willing to help and learn from others</li><li>
You will have the opportunity to apply the most recent literature to concrete AI projects with a real impact on business</li><li>
As a growing company, we combine a startup mindset with the resources necessary to commit to exciting new initiatives. At Meltwater, everyone has an opportunity to make a difference</li><li>
Enjoy flexible paid time off that allows you to have an enhanced work-life balance.</li><li>
Excellent medical, dental, and vision options</li><li>
401(k) matching, life insurance, commuter benefits, and parental leave plans</li><li>
Complimentary CalmApp subscription for you and your loved ones, because mental wellness matters.</li><li>
Energetic work environment with a hybrid work style, providing the balance you need.</li><li>
Thrive within our inclusive community and seize ongoing professional development opportunities to elevate your career.</li><li>
Total compensation range for this position: $150-200 per year (Depending on insurance)</li></ul> 

Where You'll Work: 
New York 
 
When you'll join: 
May/June 2026 
 
Our Story 
 
At Meltwater, we believe that when you have the right people in the right environment, great things happen. 
 
Our best-in-class technology empowers our 27,000 customers around the world to make better business decisions through data. But we can&rsquo;t do that without our global team of developers, innovators, problem-solvers, and high-performers who embrace challenges and find new solutions for our customers. 
 
Our award-winning global culture drives everything we do and creates an environment where our employees can make an impact, learn every day, feel a sense of belonging, and celebrate each other&rsquo;s successes along the way. 
 
We are innovators at the core who see the potential in people, ideas and technologies. Together, we challenge ourselves to go big, be bold, and build best-in-class solutions for our customers. 
 
We&rsquo;re proud of our diverse team of 2,200+ employees in 50 locations across 25 countries around the world. No matter where you are, you&rsquo;ll work with people who care about your success and get the support you need to unlock new heights in your career. 
 
We are Meltwater. Inspired by innovation, powered by people. 
 
Our Team 
 
Our AI team is young, ambitious and focused on innovation. With Meltwater, we are more than 2000 people across the globe, so there is a lot going on. We believe in diversity and inclusion, and building teams with a wide variety of backgrounds and perspectives. This approach not only raises the quality of our products for our customers, but makes collaboration along the way much more fun. 
Read our under-the-hood blog to see which problems our engineers are solving. 
 
Equal Employment Opportunity Statement 
Meltwater is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: At Meltwater, we are dedicated to fostering an inclusive and diverse workplace where every employee feels valued, respected, and empowered. We are committed to the principle of equal employment opportunity and strive to provide a work environment that is free from discrimination and harassment. 
 
All employment decisions at Meltwater are made based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, veteran status, or any other status protected by the applicable laws and regulations. 
 
Meltwater does not tolerate discrimination or harassment of any kind, and we actively promote a culture of respect, fairness, and inclusivity. We encourage applicants of all backgrounds, experiences, and abilities to apply and join us in our mission to drive innovation and make a positive impact in the world.
 
 
We may use AI to assist in aspects of our hiring process, such as reviewing candidate information and supporting evaluation activities. These tools are used only to assist our team through increased efficiencies. Every output continues to be reviewed by humans, and all hiring decisions are made by humans. We remain committed to evaluating candidates fairly, consistently, and in compliance with all applicable laws</div>

Machine Learning Engineer

James Search Group

<div>
 
 
 AI/ML Engineer
 
 
 
 
 Location:
 
 New York, NY
 
 
 
 Compensation:
 
 $135,000 &ndash; $175,000 base + bonus + full benefits, (401(k), and more)
 
 
 
 Industry:
 
 Global P&amp;C Insurance
 
 
 
 
 
 
 About the role and the company.
 
 
 
 James Search Group is working closely with a top-tier global property &amp; casualty insurance carrier to identify an
 
 AI/ML Engineer
 
 to join their enterprise Data and Artificial Intelligence division. This team is driving innovation across the business by developing and scaling AI capabilities that unlock new value and improve decision-making across underwriting, claims, and customer engagement.
 
 
 
 
 
 As an AI/ML Engineer, you'll collaborate with senior team members to build, refine, and deploy predictive models and intelligent systems. The ideal candidate is skilled in analytics, curious by nature, and passionate about transforming complex data into practical solutions that deliver measurable business impact.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Support the development and deployment of AI/ML models&mdash;including classification, forecasting, uplift and propensity modeling, and foundational model tuning.
 </li>
 <li>
 Collaborate with cross-functional teams to identify use cases where data science can enhance operational efficiency and business performance.
 </li>
 <li>
 Partner with business, IT, and strategy teams to ensure AI models are scalable, impactful, and aligned with organizational goals.
 </li>
 <li>
 Communicate analytical findings clearly to stakeholders with varying levels of technical knowledge.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline; Ph.D. a plus.
 </li>
 <li>
 Minimum of 2 years&rsquo; experience applying advanced analytics methods (e.g., decision trees, logistic regression, neural networks, random forests).
 </li>
 <li>
 Proficiency in R or Python for analytics and model development, including work with both structured and unstructured data.
 </li>
 <li>
 Proven ability to manage and integrate large, complex datasets and an understanding of end-to-end data modeling processes.
 </li>
 <li>
 Strong written and verbal communication skills with the ability to connect technical outputs to business strategy.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Internship or project experience in machine learning, AI engineering, or related roles&mdash;especially in insurance or financial services.
 </li>
 <li>
 Familiarity with actuarial concepts or insurance-specific data models.
 </li>
 <li>
 Enthusiastic about continued learning in AI/ML and staying current with new tools and methodologies.
 </li>
 <li>
 Comfortable in a collaborative, fast-paced, and agile working environment.
 </li>
 </ul>
 
 
 
 
 This is a unique opportunity to grow your career with a highly respected organization investing in next-generation analytics.
 
 
 
 
 
 
 Apply today
 
 to help reshape the future of insurance through data and AI innovation.
 
</div>

Mindrift

<div>
 
 Please submit your CV in English and indicate your level of English proficiency.
 
 
 
 Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.
 
 Participation is project-based, not permanent employment.
 
 
 
 
 What This Opportunity Involves
 
 
 
 While each project involves unique tasks, contributors may:
 
 
 <ul>
 <li>
 Design original computational STEM problems that simulate real scientific workflows
 </li>
 <li>
 Create problems that require Python programming to solve
 </li>
 <li>
 Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
 </li>
 <li>
 Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches
 </li>
 <li>
 Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn)
 </li>
 <li>
 Document problem statements clearly and provide verified correct answers
 
 
 </li>
 </ul>
 
 What We Look For
 
 
 
 This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
 
 
 <ul>
 <li>
 5+ years of hands-on machine learning experience with proven business impact
 </li>
 <li>
 Portfolio of completed projects and publications showcasing real-world problem-solving
 </li>
 <li>
 Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
 </li>
 <li>
 Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
 </li>
 <li>
 Expert with SQL and database operations for data manipulation and analysis
 </li>
 <li>
 Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
 </li>
 <li>
 Understanding of MLOps practices and model deployment workflows
 </li>
 <li>
 Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
 </li>
 <li>
 Strong written English (C1+)
 
 
 </li>
 </ul>
 
 How It Works
 
 
 
 Apply &rarr; Pass qualification(s) &rarr; Join a project &rarr; Complete tasks &rarr; Get paid
 
 
 
 Project time expectations
 
 
 
 For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
 
 
 
 Compensation
 
 
 
 On this project, contributors can earn up to
 
 $90 per hour equivalent
 
 , depending on their level and pace of contribution.
 
 
 Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
</div>

Freelance Machine Learning Engineer

Techfellow Limited

<div>
 
 
 [Up to c. $450k Comp Package | Office-Led Working]
 
 
 
 
 
 
 
 Role Overview
 
 
 
 
 
 
 We&rsquo;re partnering with a top-tier, technology-led trading firm where machine learning plays a central role in decision-making and execution. This hire will sit within a highly specialised ML group, contributing to the design and evolution of the firm&rsquo;s research and production ML ecosystem. This is a hands-on engineering role operating close to research. You&rsquo;ll help build the systems, tooling, and infrastructure that enable rapid experimentation and efficient deployment of models - while also contributing to how machine learning is applied across a fast-moving, data-rich environment...
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Design and develop infrastructure supporting model training, evaluation, and production deployment
 </li>
 <li>
 Improve research workflows to accelerate iteration speed and feedback loops for ML experimentation
 </li>
 <li>
 Build clean, scalable tooling and APIs that make ML systems intuitive and efficient to use
 </li>
 <li>
 Collaborate with researchers to translate theoretical models into robust, production-ready solutions
 </li>
 <li>
 Evaluate and apply a broad range of modelling techniques depending on the problem space
 </li>
 <li>
 Maintain high-quality, reproducible research codebases with strong usability and structure
 </li>
 <li>
 Contribute to architectural decisions shaping the firm&rsquo;s ML platform and tooling ecosystem
 </li>
 <li>
 Stay close to emerging ML techniques, frameworks, and hardware developments, integrating where valuable
 </li>
 </ul>
 
 
 
 
 
 What You&rsquo;ll Bring&hellip;
 
 
 
 
 
 <ul>
 <li>
 3-8 years&rsquo; experience in machine learning engineering, applied ML, or similar technical roles
 </li>
 <li>
 Strong academic or practical grounding in mathematics (e.g. optimisation, linear algebra, probability)
 </li>
 <li>
 Experience building ML systems end-to-end, from experimentation through to production deployment
 </li>
 <li>
 Hands-on experience with modern ML frameworks (e.g. PyTorch, JAX, TensorFlow or similar)
 </li>
 <li>
 Proven ability to structure and maintain clean, reliable, and reproducible research code
 </li>
 <li>
 Solid software engineering fundamentals, including system design and API development
 </li>
 <li>
 Genuine interest in state-of-the-art ML research and willingness to explore new techniques
 </li>
 <li>
 Ability to critically assess modelling approaches and choose appropriate methods for different problems
 </li>
 <li>
 Strong communication skills and ability to collaborate closely with researchers and engineers
 </li>
 </ul>
 
 
 
 
 ...
 
</div>

Machine Learning Platform Engineer (Research-Focused) | Technology-Driven Quantitative Trading Firm

Stott and May

<div>
 
 
 Data Scientist / Data Engineer (Ecommerce) Contract Opportunity
 
 
 
 
 
 
 
 Work:
 
 
 
 We&rsquo;re supporting an ecommerce client looking for a hybrid
 
 Data Scientist / Data Engineer
 
 contractor to help scale data products and drive insights across customer, product, and digital performance data.
 
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Build and maintain data pipelines supporting analytics and machine learning use cases
 </li>
 <li>
 Develop models and analyses around customer behavior, recommendations, forecasting, and conversion optimization
 </li>
 <li>
 Work with large-scale ecommerce data (clickstream, transactions, inventory, marketing)
 </li>
 <li>
 Design and optimize datasets for reporting, experimentation, and predictive modeling
 </li>
 <li>
 Partner with analytics, product, and engineering teams to productionize solutions
 </li>
 <li>
 Support data quality, performance tuning, and scalable data architecture
 </li>
 </ul>
 
 
 Requirements:
 
 
 <ul>
 <li>
 Strong Python and SQL skills
 </li>
 <li>
 Experience in both data engineering and data science / ML workflows
 </li>
 <li>
 Background building pipelines with tools like Airflow, Spark, dbt, or similar
 </li>
 <li>
 Experience with cloud platforms such as AWS, GCP, or Azure
 </li>
 <li>
 Exposure to recommendation systems, forecasting, customer analytics, or experimentation (A/B testing) preferred
 </li>
 <li>
 Ecommerce, retail, or marketplace data experience strongly preferred
 </li>
 </ul>
 
 
 Details:
 
 
 <ul>
 <li>
 Fully remote
 </li>
 <li>
 40 hours/week (full-time
 
 contract
 
 )
 </li>
 <li>
 Initial 6-month
 
 contract
 
 with likely extension
 </li>
 <li>
 W2 or personal LLC only (
 
 no C2C
 
 )
 </li>
 <li>
 Rates competitive and dependent on experience (target $80&ndash;$110/hr)
 </li>
 </ul>
 
 
</div>

Data Scientist

JPMorganChase

<div>JOB DESCRIPTION 
Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team
As a Software Engineer III (Machine Learning Platform Engineer) at JPMorgan Chase within the Consumer &amp; Community Banking (CCB) line of business, you serve as a seasoned member of an agile team focused on building, scaling, and maintaining robust machine learning platforms. You will design and deliver trusted, market-leading infrastructure and tools that empower data scientists and ML engineers to develop, deploy, and monitor models efficiently and securely. You are responsible for implementing critical technology solutions across multiple technical areas to support the firm&rsquo;s business objectives and drive innovation in ML platform capabilities.
Job responsibilities<ul><li>
Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows.</li><li>
Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.</li><li>
Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions.</li><li>
Implement secure, high-quality production code for platform services, APIs, and automation pipelines.</li><li>
Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations.</li><li>
Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement.</li><li>
Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.</li><li>
Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.</li><li>
Contribute to the ML platform engineering community of practice and participate in events that explore new and emerging technologies.</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Formal training or certification on software engineering concepts and 3+ years applied experience</li><li>
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure</li><li>
Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
</li><li>Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
</li><li>Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure</li><li>
Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring</li><li>
Experience developing APIs and platform services for ML workflows
</li><li>Solid knowledge of the software development life cycle and agile methodologies
</li><li>Ability to collaborate with cross-functional teams to deliver platform solutions aligned with business objectives
</li></ul>Preferred qualifications, capabilities, and skills<ul><li>
Familiarity with Databricks for scalable data engineering and ML platform integration</li><li>
Experience working with Snowflake for cloud-based data warehousing and analytics</li><li>
Exposure to Snorkel AI for programmatic data labeling and training data management</li><li>
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)</li><li>
Familiarity with feature stores, model registries, and ML metadata management</li><li>
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)</li><li>
Experience with RESTful APIs and microservices architectures</li></ul>
ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
<div>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div><div> 
 
</div><div>The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.</div></div>

Software Engineer III - Machine Learning Platform

Catalyst Labs

<div>
 
 About The Job ML Engineer
 
 
 
 
 Our Client
 
 
 
 Is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs.
 
 
 By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.
 
 
 
 About Us
 
 
 
 Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that&rsquo;s deeply embedded in our clients&rsquo; recruitment operations.
 
 
 We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.
 
 
 
 Location
 
 : New York, NY
 
 
 
 Work type
 
 : Full Time,
 
 
 
 Compensation
 
 : above market base + bonus + equity
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
 </li>
 <li>
 Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
 </li>
 <li>
 Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
 </li>
 <li>
 Build agents capable of operating natively on real-world audio inputs.
 </li>
 <li>
 Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
 </li>
 <li>
 Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
 </li>
 <li>
 Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
 </li>
 <li>
 Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
 </li>
 <li>
 1-6 years of professional experience in ML engineering.
 </li>
 <li>
 Strong programming skills in Python (TypeScript experience is a plus).
 </li>
 <li>
 Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Familiarity with cloud environments and infrastructure (preferably AWS).
 </li>
 <li>
 Strong understanding of data pipeline design, real-time inference, and model monitoring.
 </li>
 <li>
 Excellent communication skills with the ability to engage directly with customers and stakeholders.
 
 
 </li>
 </ul>
 
 Core Experience
 
 
 
 <ul>
 <li>
 Proven experience building and deploying ML models into production environments.
 </li>
 <li>
 Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
 </li>
 <li>
 Experience with audio-focused ML projects or similar domains involving unstructured data.
 </li>
 <li>
 Proficiency in building scalable data pipelines for model training and evaluation.
 </li>
 <li>
 Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
 </li>
 <li>
 Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
 </li>
 </ul>
</div>

ML Engineer

Explore 735+ Machine learning engineer in New York this May. Find roles across top companies and apply now to boost your career.

735 machine learning engineer jobs In New York

Machine Learning Engineer

Machine Learning Engineer

Freelance Machine Learning Engineer

Machine Learning Platform Engineer (Research-Focused) | Technology-Driven Quantitative Trading Firm

Data Scientist

Software Engineer III - Machine Learning Platform

ML Engineer