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Colgate-Palmolive

<div></div><div><div><div>Requisition ID <b>174332</b> - Posted <b>06/18/2026</b> - <b>Analytics</b> - <b>United States</b> - <b>New York</b> - <b>New York</b> - <b>Colgate-Palmolive</b> - <b>Travel - up to 10% of time</b> - <b>On-site</b></div></div><p></p><div><div><div><div><p><b><br>
</b></p></div></div></div></div><br>
<div></div><div><div><div><div><div><div><div>No Relocation Assistance Offered<br>
Job Number #174332 - New York, New York, United States<br>
<br>
<b>Who We Are</b><br>
<br>
Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!<br>
<br>
Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values&mdash;Caring, Inclusive, and Courageous&mdash;we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.</div><br>
<div><b>*This role can sit in our Park Ave (NYC) or Piscataway, NJ office*</b></div><br>
<div></div>
<div><b>
Role Summary</b></div>
<p>
We are seeking a Machine Learning Engineer who brings the analytical rigor of a data scientist and the engineering discipline of a software architect. In support of Colgate-Palmolive&rsquo;s purpose to Make More Smiles and our commitment to a healthier future for our people, pets, and planet, this role builds the advanced machine learning capabilities that power smarter decisions, accelerate innovation, and create measurable impact across our global enterprise.</p>
<p>
As part of the Enterprise AI/ML Center of Excellence, you will lead the architectural design and end-to-end execution of high-priority ML initiatives. This involves integrating statistical modeling, optimization, and autonomous workflows into Colgate-Palmolive's business processes to accelerate innovation, enhance decision intelligence, and embed AI. Beyond hands-on technical work, you ensure solutions are architecturally sound, production-ready, and compliant with enterprise governance standards, translating strategy into robust execution aligned with stakeholder needs and long-term value creation.</p><br>
<div></div>
<div><b>
Responsibilities:</b></div>
<ul>
<li><div>Productionize ML Research: Transition experimental models into robust, scalable production services. You don't just build the model; you build the pipeline that sustains it.</div>
</li>
<li><div>Pipeline Orchestration: Design and maintain complex data and ML pipelines using Airflow and dbt to ensure data integrity and model reliability.</div>
</li>
<li><div>Statistical Rigor: advanced statistical modeling and hypothesis testing to validate models, ensuring outcomes are testable and honest.</div>
</li>
<li><div>DevOps &amp; MLOps: Utilize modern developer tools to work within and CI/CD frameworks for ML and software lifecycle management</div></li></ul><br>
<div>
</div><div><b>Required Qualifications:</b></div>
<ul>
<li><div>Bachelor&rsquo;s Degree (or higher) in a high-rigor field: Statistics, Physics, Chemistry, Mathematics, Data Science, or Computer Science with a heavy emphasis on Statistical Learning.</div>
</li>
<li><div>Experience: Bachelors degree: 6+ of years of technical experience; Masters or PhD (3+ years)</div></li></ul><br>
<div>
</div><div><b>Preferred Qualifications:</b></div>
<ul>
<li><div>Proven expertise in Data Science and/or Machine Learning Engineering.</div>
</li>
<li><div>Advanced proficiency in Python (Production-grade) and SQL.</div>
</li>
<li><div>Hands-on experience with Airflow for orchestration and dbt for transformation.</div>
</li>
<li><div>Familiarity with modern IDEs and Agentic Coding systems (e.g., Cursor, Windsurf, Claude Code, Antigravity) to maximize output velocity.</div>
</li>
</ul><ul><li><div>Modern Stack: Expert knowledge of Python, Scikit-learn, major ML Libraries</div>
</li>
<li><div>Data Engineering: Deep understanding of data lifecycle (ETL/ELT), data architecture, best practices for templatized data transformation</div>
</li>
<li><div>Engineering Excellence: Familiar with Docker/Kubernetes, CI/CD, Git, and &quot;Software Engineering for ML&quot; best practices.</div>
</li>
<li><div>LLM Literacy: Familiar with concepts underpinning LLMs, and strategies to integrate GenAI into MLE project lifecycle</div></li><br>
</ul>
<div><br>
<b>Compensation and Benefits</b><br>
Salary Range $130,000.00 - $170,000.00 USD<br>
<br>
Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.<br>
<br>
Benefits: Salaried employees enjoy a comprehensive benefits package, including medical, dental, vision, basic life insurance, paid parental leave, disability coverage, and participation in the 401(k) retirement plan with company matching contributions subject to eligibility requirements. Additional benefits include a minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours) and 13 paid holidays (vacation days are prorated based on the employee's hire date within the calendar year). Paid sick leave is adjusted based on role and location in accordance with local laws. Detailed information regarding paid sick leave entitlements will be provided to employees upon hiring and may be subject to adjustments based on changes in legislation or company policies.<br>
<br>
<b>Our Commitment to Inclusion</b><br>
Our journey begins with our people&mdash;developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business.<br>
<br>
<b>Equal Opportunity Employer</b><br>
Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law.<br>
<br>
Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation.<br>
<br>
For additional Colgate terms and conditions, please click here.<br>
<br>
#LI-On-site</div></div></div></div></div></div></div></div><p></p>

Machine Learning Engineer (174332)

NYU Langone Health

<div><p>NYU Grossman School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge.
<br>
<br>
<i>For more information, go to</i> <i>med.nyu.edu</i>, and interact with us on <i>LinkedIn</i>, <i>Glassdoor</i>, <i>Indeed</i>, <i>Facebook</i>, <i>Twitter</i> <i>and</i> <i>Instagram</i>.</p>
<p><b>
Position Summary:</b><br>
We have an exciting opportunity to join our team as a Engineer II - Applied AI.
</p><p>As a ML Engineer, you will support the implementation of diverse Generative AI and Machine Learning initiatives across the health system. You will be responsible for driving specific projects forward in collaboration with the key customers - data scientists, business units and IT partners across the various verticals (corporate services, office of science and research, clinical, and pathology).</p>
<p><b>
Job Responsibilities:</b></p>
<div>
<ul><li>Design and implement AI/ML applications using tools and frameworks from our teams technology stack and following the best practices in software development</li>
</ul></div><div><ul><li>Collaborate with data scientists to build and / or fine-tune high performing AI models and implement modern techniques from relevant published papers</li>
</ul></div><div><ul><li>Develop scalable and robust pipelines to support large data processing tasks</li>
</ul></div><div><ul><li>Implement our internal security and data protection standards in AI applications; assist the team with maintaining emerging AI system risk and security standards</li>
</ul></div><div><ul><li>Support the team in preparation for technical reviews and internal documentation (architecture, IT Security, AI)</li>
</ul></div><div><ul><li>Collaborate with other team members and stakeholders to meet team objectives; develop understanding of business workflows shadow / work with clients to gather feature requirements, identify and document AI opportunities, create appropriate tickets, participate in backlog refinement, execute tickets, participate in code-review activities</li>
</ul></div><div><ul><li>Stay updated with the latest industry trends and advancements in AI and relevant cloud technologies; routinely share and demonstrate learnings with the team</li>
</ul></div><div><ul><li>Provide technical guidance and coaching to less experienced team members</li>
</ul></div><div><ul><li>Participate in all phases of AI software development life cycle, including functional analysis, prototyping, development, evaluation, testing, deployment, refactoring and technical support</li></ul></div><br>
<p>
</p><p><b>Minimum Qualifications:</b><br>
To qualify you must have a 1. Bachelor's degree in computer science, software engineering, or a related field.<br>
2. At least 1-3 years of hands-on experience in AI Solution development<br>
3. Strong programming skills in Python, or other languages commonly used in AI development.<br>
4. Substantial knowledge of AI, machine learning, and deep learning<br>
5. Experience with AI platforms like PyTorch or TensorFlow<br>
6. Experience with building large-scale and/or compute-intensive applications on clusters for data engineering, model training and evaluation (HPC, Spark, Kubernetes)<br>
7. Understanding of software development principles and methodologies, including data structures, data modeling and software architecture.<br>
8. Excellent problem-solving skills and ability to work in a team environment.<br>
9. Excellent communication skills, both verbal and written.</p>
<p><b>
Preferred Qualifications:</b><br>
1. Masters degree in computer science, data science, software engineering, or a related quantitative discipline<br>
2. 3-5 years of hands-on experience in AI Solution development<br>
3. Basic understanding of at least one cloud (Azure, AWS, GCP) and cloud native development tools, and experience using their AI / ML toolchain</p>
<p><i>
Qualified candidates must be able to effectively communicate with all levels of the organization.</i>
<br>
<br>
NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.
<br>
<br>
NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.
<br>
<br>
View Know Your Rights: Workplace discrimination is illegal.</p>
<p>
NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $84,577.92 - $126,000.00 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.</p>
<p>
To view the Pay Transparency Notice, please click here</p></div>

Machine Learning Engineer

Capgemini

<div><div><div><div><p>Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.</p>
<div><div><div><h2 class="jobSectionHeader"><b>Location: Jersey City, NJ or NYC, NY (Hybrid).</b></h2>
</div></div><div></div><div><div><h2 class="jobSectionHeader"><b>Job Description</b></h2>
</div><div><ul><li>Demonstrated expertise and a strong foundational background in Artificial Intelligence AI and Machine Learning ML including proficiency with current industry trends and methodologies</li>
<li><div>Proven track record of successfully delivering AIML projects from inception to deployment prior experience within the financial sector is highly desirable</div>
</li><li><div>Solid programming skills particularly in Python including scripting development and data manipulation</div>
</li><li><div>Exceptional communication and interpersonal skills with the ability to articulate complex technical concepts and present effectively to diverse audiences across all organizational levels.</div>
</li></ul></div></div></div><p>The base compensation range for this role in the posted location is: 85,000 - 95,000</p>
<p>Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.</p>
<p>The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.</p>
<p>These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.</p>
<p>It is not typical for candidates to be hired at or near the top of the posted compensation range.</p>
<p>In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.</p><br>
<p></p><p><b>Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.</b> In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:</p>
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul><p><b>Important Notice:</b> Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.</p><br>
<p></p><p><b>Disclaimers</b></p>
<p>Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.</p>
<p>This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.</p>
<p>Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.</p>
<p>Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law</p><br>
<p></p><p>Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</p></div></div></div></div><p></p>

Fusemachines

<div>
 <strong>
  About Fusemachines
  <br/>
  <br/>
 </strong>
 Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 <br/>
 <br/>
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 <br/>
 <br/>
 <strong>
  Type: Full-time, Remote
  <br/>
  <br/>
 </strong>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We&rsquo;re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You&rsquo;ll work across the ML lifecycle&mdash;from problem framing and data exploration to model development, evaluation, deployment, and monitoring&mdash;often in partnership with client stakeholders and internal delivery teams.
 <br/>
 <br/>
 You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Problem Framing &amp; Stakeholder Partnership
  </li>
  <ul>
   <li>
    Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)
   </li>
   <li>
    Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)
   </li>
  </ul>
  <li>
   Data Analysis &amp; Feature Engineering
  </li>
  <ul>
   <li>
    Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses
   </li>
   <li>
    Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices
   </li>
   <li>
    Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions
   </li>
  </ul>
  <li>
   Model Development (Core ML)
  </li>
  <ul>
   <li>
    Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)
   </li>
   <li>
    Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation
   </li>
   <li>
    Build time series models (statistical and ML/DL approaches) and validate with proper backtesting
   </li>
   <li>
    Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness
   </li>
   <li>
    Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making
   </li>
  </ul>
  <li>
   Deep Learning
  </li>
  <ul>
   <li>
    Build and train deep learning models using PyTorch or TensorFlow/Keras
   </li>
   <li>
    Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)
   </li>
  </ul>
  <li>
   Evaluation, Explainability, and Iteration
  </li>
  <ul>
   <li>
    Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports
   </li>
   <li>
    Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence
   </li>
  </ul>
  <li>
   Productionization &amp; MLOps (Project-Dependent)
  </li>
  <ul>
   <li>
    Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration
   </li>
   <li>
    Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans
   </li>
  </ul>
  <li>
   Documentation &amp; Communication
  </li>
  <ul>
   <li>
    Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders
   </li>
   <li>
    Create documentation and lightweight demos that make results actionable
    <br/>
   </li>
  </ul>
 </ul>
 Success in This Role Looks Like
 <br/>
 <br/>
 <ul>
  <li>
   You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)
  </li>
  <li>
   Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring
  </li>
  <li>
   Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)
  </li>
  <li>
   Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)
  </li>
  <li>
   Strong SQL skills (joins, window functions, aggregation, performance awareness)
  </li>
  <li>
   Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset
  </li>
  <li>
   Hands-on experience across multiple model types, including:
  </li>
  <ul>
   <li>
    Classification &amp; regression
   </li>
   <li>
    Time series forecasting
   </li>
   <li>
    Clustering/segmentation
   </li>
  </ul>
  <li>
   Experience with deep learning in PyTorch or TensorFlow/Keras
  </li>
  <li>
   Strong problem-solving skills: ability to work with ambiguous goals and messy data
  </li>
  <li>
   Clear communication skills and ability to translate analysis into decisions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)
  </li>
  <li>
   Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)
  </li>
  <li>
   Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)
  </li>
  <li>
   Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)
  </li>
  <li>
   Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)
  </li>
  <li>
   Consulting or client-facing delivery experience
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Certifications (Strong Plus)
  <br/>
  <br/>
 </strong>
 Candidates with at least one relevant certification are especially encouraged to apply:
 <br/>
 <br/>
 <ul>
  <li>
   Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks)
  </li>
  <li>
   Databricks certifications (Data Scientist, Data Engineer, or related)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)
  </li>
  <li>
   Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products
  </li>
  <li>
   Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  <em>
   Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
   <br/>
   <br/>
  </em>
 </em>
 Important: Immigration Sponsorship Policy
 <br/>
 <br/>
 Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including:
 <br/>
 <br/>
 <ul>
  <li>
   Direct Company Sponsorship: Such as H-1B, J-1, or TN visas
  </li>
  <li>
   Employer of Record: Listing Fusemachines as the immigration employer on any government documentation
  </li>
  <li>
   Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT)
   <br/>
   <br/>
  </li>
 </ul>
 Powered by JazzHR
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 <br/>
 qUN1H2divA
</div>


Machine Learning Engineer / Data Scientist

Spotify

<div><div><div><div><div><div>Engineering</div></div></div><div><div>
Machine Learning</div></div></div><div><div>
Permanent</div></div><div><div>
New York</div></div><div><div><div>
<div>We design Spotify&rsquo;s consumer experience&mdash;end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints&mdash;from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.<br>
<br>
The Verbatim squad sits within the Enrichment &amp; Content Intelligence product area and is focused on helping Spotify better understand audio, text, and visual content through machine learning. The team develops technologies that power experiences across Spotify including content skipping, transcription, moderation, and visual understanding. Working at the intersection of large-scale machine learning and product innovation, the squad partners closely with Product, Engineering, and Data Science teams to build intelligent systems that improve how users experience content across the platform.</div>
</div></div></div></div><div><div><p>
What You'll Do</p><ul><div>
<ul>
<li>Lead end-to-end machine learning initiatives from ideation and prototyping through experimentation, deployment, and large-scale productionization.</li>
<li>Design, develop, and deploy machine learning systems that operate across hundreds of millions of content signals using both real-time and batch processing architectures.</li>
<li>Advance Spotify&rsquo;s capabilities in natural language understanding, multimodal AI, and content intelligence.<br>
Build and evaluate LLM-powered solutions using modern prompting techniques, retrieval systems, and advanced model orchestration approaches.</li>
<li>Define rigorous evaluation methodologies including golden datasets, precision and recall frameworks, offline benchmarking, and online experimentation.</li>
<li>Partner closely with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists to influence technical strategy and roadmap decisions.</li>
<li>Mentor engineers across the organization and help elevate machine learning engineering standards and best practices.</li>
<li>Contribute to the adoption of AI-assisted development workflows and tooling that improve team productivity and engineering effectiveness.</li>
</ul>
</div></ul></div></div><div><div><p>Who You Are</p><ul><div>
<ul>
<li>You have solid experience developing and deploying machine learning systems in production environments.</li>
<li>You have successfully delivered large-scale machine learning architectures operating on substantial datasets and high-throughput production systems.</li>
<li>You have deep experience with machine learning, deep learning, and modern AI technologies.</li>
<li>You have hands-on experience working with large language models and understand how to evaluate, adapt, and deploy them effectively for real-world product challenges.</li>
<li>You have experience building evaluation frameworks and can quantify model performance through robust experimentation and measurement techniques.</li>
<li>You know how to navigate ambiguity and make thoughtful technical trade-offs that balance product impact, scalability, and engineering quality.</li>
<li>You have experience influencing technical direction across cross-functional teams and can communicate complex machine learning concepts to diverse audiences.</li>
<li>You care about developing others and enjoy mentoring engineers through technical guidance and collaboration.</li>
<li>You have experience working with NLP, prompt engineering, retrieval-augmented generation (RAG), vector databases, or multimodal machine learning systems.</li>
<li>You are curious about emerging AI technologies and excited about integrating tools such as Claude Code, Cursor, and other AI-assisted development capabilities into engineering workflows.</li>
</ul>
</div></ul></div></div><div><div><p>Where You'll Be</p><ul><div>
<ul>
<li>This role is based in New York City</li>
<li>We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.</li>
</ul>
</div></ul></div></div><div><div><p>Learn about life at Spotify</p></div><div><div>
<div>
The United States base range for this position is $184,049&ndash;262,928 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.</div>
</div></div></div><div><div><p>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Senior Machine Learning Engineer, Content Intelligence

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience.</li>
<li>5 years of experience programming in Python.</li>
<li>Experience with training machine learning models.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>PhD in Computer Science or equivalent field.</li>
<li>5 years of experience with data structures/algorithms.</li>
<li>Experience publishing in venues (e.g., NeurIPS, ICML, COLT, ICLR) or contributing to open-source projects related to ML.</li>
<li>Experience with ML frameworks (JAX, PyTorch) for large-scale model training.</li>
<li>Experience applying ML research to generative models, specifically in areas of post-training Gemini models.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p></p>
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
<br>
<br>
US: $174000 - $253000 (USD) + 15% bonus target + bonus + equity + benefits<br>
<br>
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Prototype and test fundamental algorithmic approaches. Write and test product or system development code.<br>
</li>
<li>Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,) and bring solutions into production environments<br>
</li>
<li>Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.<br>
</li>
<li>Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.<br>
</li>
<li>Design and implement solutions in one or more specialized ML areas such as reinforcement learning, optimization, privacy, and game theory.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Software Engineer, Foundational ML Research

<div>
 <strong>
  Minimum qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics or a related field and 2 years of experience in the job offered or in a Software Engineer-related occupation.
  </li>
  <li>
   Position requires 2 years of experience in the following: Applying machine learning, statistics, or diffusion model theory in applied research; Software development using Java, C, C++, Python, or Go; Designing and applying data structures or algorithms; ML infrastructure management including model evaluation and data processing; Data analysis and synthesis to generate solutions or evaluate outcomes for machine learning applications
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 The US base salary range for this full-time position is $147,000 - $211,000 + 15% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google .
 <br/>
 <br/>
 Position reports to the Google New York, NY office &amp; may allow for a hybrid schedule as per Google policy.
 <br/>
 <br/>
 Artificial intelligence will be one of humanity&rsquo;s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
 <br/>
 <br/>
 We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Apply research to high-impact problems by prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning
  </li>
  <li>
   Develop and test robust product code, performing comprehensive testing that includes integration, performance, and security to ensure system quality and reliability
  </li>
  <li>
   Collaborate with peers through rigorous design and code reviews to enforce best practices, improve system testability, and ensure overall efficiency and accuracy
  </li>
  <li>
   Triage and resolve complex system issues by debugging, analyzing root causes, and implementing solutions to optimize hardware, network, and service operations
  </li>
  <li>
   Create and maintain technical documentation and educational materials, adapting content based on product updates and user feedback to ensure clarity and relevance. Manage the full deployment lifecycle by contributing to system qualification, monitoring, process automation, and paying down technical debt to improve long-term scalability
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>


Software Engineer

Explore 167+ Machine learning engineer in New York this July. Find roles across top companies and apply now to boost your career.

167 machine learning engineer jobs In New York

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