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ai engineer

ai ml engineer fully remote upto 85 hr

Mercor

<div>
 
 About The Job
 
 
 
 
 Mercor
 
 connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
 
 Benchmark
 
 ,
 
 General Catalyst
 
 ,
 
 Peter Thiel
 
 ,
 
 Adam D'Angelo
 
 ,
 
 Larry Summers
 
 , and
 
 Jack Dorsey
 
 .
 
 
 
 Position:
 
 ML Engineer (Coding Agent Experience)
 
 
 
 Type:
 
 
 Contract
 
 
 
 
 Compensation:
 
 
 $85/hour
 
 
 
 
 Location:
 
 
 Remote
 
 
 
 
 Role Responsibilities
 
 
 
 <ul>
 <li>
 Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
 </li>
 <li>
 Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
 </li>
 <li>
 Identify bugs, edge cases, performance issues, and failure modes in AI models.
 </li>
 <li>
 Compare outputs from multiple frontier models and assess their strengths and weaknesses.
 </li>
 <li>
 Apply professional engineering judgment to realistic ML engineering scenarios.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Must-Have
 
 
 
 <ul>
 <li>
 2+ years of professional machine learning engineering experience.
 </li>
 <li>
 Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
 </li>
 <li>
 Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
 </li>
 <li>
 Ability to evaluate model-generated machine learning implementations and technical tradeoffs.
 
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience deploying ML systems to production.
 
 
 
 </li>
 </ul>
 
 Compensation &amp; Legal
 
 
 
 <ul>
 <li>
 $400 per accepted task
 </li>
 <li>
 Compensation is tied to accepted work.
 
 
 
 </li>
 </ul>
 
 Application Process (Takes 20&ndash;30 mins to complete)
 
 
 
 <ul>
 <li>
 Upload resume
 </li>
 <li>
 AI interview based on your resume
 </li>
 <li>
 Submit form
 
 
 
 </li>
 </ul>
 
 Resources &amp; Support
 
 
 
 <ul>
 <li>
 For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
 </li>
 <li>
 For any help or support, reach out to: support@mercor.com
 
 
 
 </li>
 </ul>
 
 PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 
</div>

AI/ML Engineer - Fully Remote | Upto $85/hr

Fusemachines

<div>
 
 About Fusemachines
 
 
 
 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.
 
 
 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.
 
 
 
 Type: Full-time, Remote
 
 
 
 
 Role Overview
 
 
 
 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.
 
 
 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.
 
 
 
 Key Responsibilities
 
 
 
 <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
 
 </li>
 </ul>
 </ul>
 Success in This Role Looks Like
 
 
 <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
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <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
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <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
 
 
 </li>
 </ul>
 
 Certifications (Strong Plus)
 
 
 
 Candidates with at least one relevant certification are especially encouraged to apply:
 
 
 <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)
 
 
 </li>
 </ul>
 
 Nice-to-Have
 
 
 
 <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
 
 
 </li>
 </ul>
 
 
 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.
 
 
 
 
 Important: Immigration Sponsorship Policy
 
 
 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:
 
 
 <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)
 
 
 </li>
 </ul>
 Powered by JazzHR
 
 
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</div>

Machine Learning Engineer / Data Scientist

Edra

<div>
 
 About Edra
 
 
 
 Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.
 
 
 We're a Series A startup, backed by Sequoia and other leading VC firms, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build.
 
 
 
 The Role
 
 
 
 We're looking for Backend Engineers who care deeply about the craft of building software: strong typing, thoughtful API design, robust data modeling, and systems that are a pleasure for other engineers to work with. You won't be building AI models, you'll be building everything around them: the platform, workflows, interfaces, integrations, and observability that make our AI useful in the real world. As an early engineer at Edra, you'll shape not just the product but the engineering culture, tooling choices, and technical foundations the company is built on.
 
 
 We work deliberately and deeply. There's no separation between "building it" and "shipping it"--you'll go from whiteboard to production and own the outcome. We'd rather build something thoughtfully than ship something fragile, and we treat velocity and quality as complementary, not competing.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design and build platform systems in Python (Fast API), from API contracts to database schema and infrastructure
 </li>
 <li>
 Build and maintain connectors, integrations, and data pipelines that connect our platform to external systems
 </li>
 <li>
 Build internal libraries, tooling, and interfaces that make the rest of the engineering team more productive
 </li>
 <li>
 Own your work fully: gather context, manage dependencies, and drive tasks to completion without a product manager handing you tickets
 </li>
 <li>
 Wear multiple hats across the stack&ndash;you might design a schema in the morning, build the API layer in the afternoon, and debug a deployment issue before end of day
 </li>
 <li>
 Participate in weekly product meetings, understand how customers and forward deployed engineers use what you build, and shape what gets built next
 </li>
 <li>
 Collaborate daily with a small, high-caliber team of engineers and AI specialists
 </li>
 <li>
 Have direct influence on technical direction: choose tools, set patterns, and establish conventions the team will build on for years
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 3+ years of experience in software engineering (but a computer science degree is not necessarily required)
 </li>
 <li>
 A love of writing Python and/or TypeScript to a genuinely high standard&ndash;well-modeled, well-typed, and well-documented. Strong typing feels like a superpower, not a chore
 </li>
 <li>
 Experience building libraries, SDKs, or internal tooling that made other developers' lives easier (and you&rsquo;ve enjoyed it)
 </li>
 <li>
 You light up when designing a clean database schema and take real pride in getting data models right
 </li>
 <li>
 You're at your best when you own a problem end to end &mdash; comfortable with ambiguity and energized by turning a vague problem into a well-scoped solution
 </li>
 <li>
 You're drawn to building foundational systems from scratch &mdash; greenfield work where your decisions compound over time excites you
 
 
 </li>
 </ul>
 Don't meet all of the above? We'd still love to hear from you. We're looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets. If your primary interest is building agentic systems, working with LLMs, or doing applied ML, check out our AI Engineering role&ndash;it might be a better fit.
 
 
 
 Learn More About Edra
 
 
 
 <ul>
 <li>
 Watch our Series A announcement video
 </li>
 <li>
 Read our blog post from our launch
 </li>
 <li>
 Learn more about what we're building
 
 
 </li>
 </ul>
 
 A Few Details
 
 
 
 Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.
 
 
 Compensation Range: $195K - $275K
 
 
</div>

Software Engineer - Back End (New York)

Alignerr

<div>
 
 English Audio Transcription Specialist (AI Training)
 
 
 
 
 About The Role
 
 
 
 What if your sharp ear and command of English could directly shape how AI listens to and understands the spoken word? We're looking for English Audio Transcription Specialists in the New York metro area to convert spoken audio into accurate, well-formatted text &mdash; helping AI systems learn to process real human speech with all its accents, nuances, and complexity.
 
 
 This is a fully remote, flexible contract role. No prior transcription or AI experience is required &mdash; just excellent English listening skills, strong attention to detail, and a reliable internet connection.
 
 
 <ul>
 <li>
 Organization: Alignerr
 </li>
 <li>
 Type: Hourly Contract
 </li>
 <li>
 Location: Remote
 </li>
 <li>
 Commitment: 10&ndash;40 hours/week
 
 
 </li>
 </ul>
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Listen to audio recordings in English and produce precise, verbatim transcriptions
 </li>
 <li>
 Accurately capture spoken content including natural speech patterns, filler words, and speaker changes where required
 </li>
 <li>
 Apply consistent formatting, punctuation, and spelling conventions according to project guidelines
 </li>
 <li>
 Identify and flag unclear, inaudible, or ambiguous audio segments
 </li>
 <li>
 Handle a diverse range of audio types &mdash; conversations, interviews, lectures, podcasts, customer interactions, and more
 </li>
 <li>
 Review and proofread transcriptions for accuracy, completeness, and adherence to style guides
 </li>
 <li>
 Work independently and asynchronously &mdash; fully on your own schedule
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Native or near-native fluency in English with excellent listening comprehension
 </li>
 <li>
 Strong written English skills &mdash; confident with grammar, spelling, and punctuation
 </li>
 <li>
 Naturally detail-oriented with a consistent, methodical approach to work
 </li>
 <li>
 Able to follow structured guidelines and apply them accurately at scale
 </li>
 <li>
 Comfortable working with different accents, speaking speeds, and audio quality levels
 </li>
 <li>
 Self-motivated and reliable when working independently
 </li>
 <li>
 No prior transcription, AI, or tech experience required
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience in transcription, closed captioning, subtitling, or stenography
 </li>
 <li>
 Familiarity with transcription tools or audio editing software
 </li>
 <li>
 Background in linguistics, journalism, communications, or media production
 </li>
 <li>
 Experience working with varied English dialects and accents (American, British, Australian, Indian, etc.)
 </li>
 <li>
 Fast, accurate typing skills (70+ WPM)
 </li>
 <li>
 Knowledge of specialized vocabulary in fields such as medicine, law, technology, or finance
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects alongside leading research labs
 </li>
 <li>
 Fully remote and flexible &mdash; work when and where it suits you
 </li>
 <li>
 Freelance autonomy with the structure of meaningful, task-based work
 </li>
 <li>
 Contribute to AI development that directly improves how technology understands human speech
 </li>
 <li>
 Build skills in a high-demand field at the intersection of language and AI
 </li>
 <li>
 Potential for ongoing work and contract extension as new projects launch
 </li>
 </ul>
</div>

English Audio Transcription Specialist

Databricks

<div><h1 class="jobSectionHeader">Staff Machine Learning Engineer, CustomerLake (ML/LLM)</h1>
RDQ427R109 
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems &mdash; from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers &mdash; and customer obsessed &mdash; we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. 
As one of the first engineers in the NYC Engineering office, you'll join a small, nimble team building new products from the ground up. We're building CustomerLake, the Customer Data Platform on Databricks, to bring enterprise-grade ML and AI personalization to every company whose data already lives on Databricks. The best B2C and B2B brands have historically relied on in-house ML/AI teams to power personalization, recommendations, churn and lifetime-value modeling, and audience targeting. Our goal is to deliver that same capability to companies that don't have an in-house team but already have their data in order on Databricks. This is a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks. 
The impact you'll have:
<ul><li>Evaluate ML and LLM approaches for CustomerLake's personalization use cases, push the models and algorithms forward, and continuously improve quality over time</li>
<li>Go deep on how models behave in production: inspect individual traces, understand how the models reason, and tune and improve from there</li>
<li>Build the platform and evaluation framework that let CustomerLake customers optimize for real business value such as purchases, retention, and product usage, not vanity metrics like email opens and clicks</li>
<li>Push the team toward new directions and novel methods worth tackling, not just optimizing what already exists</li>
<li>Partner closely with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions</li>
<li>Set the technical foundation and best practices for our ML/AI personalization work as we grow this into several roles across our products over the next 1-2 years</li></ul> 
What we look for:
<ul><li>10+ years of engineering experience, with a strong foundation across the full loop of shipping and improving ML/AI products</li>
<li>Hands-on experience building and evaluating ML models and/or LLM systems for real product or business use cases; your understanding is practical, not purely academic, and you can make models work well inside a product</li>
<li>Experience with personalization based on customer behavior (ideal) or transactions (acceptable), such as recommendations, targeting, churn, or lifetime-value modeling</li>
<li>Proficiency in Python and modern ML frameworks (e.g., PyTorch), with hands-on experience in model evaluation and monitoring AI quality in production</li>
<li>Familiarity with LLMs and generative AI, including techniques like retrieval-augmented generation (RAG), prompt design, fine-tuning, and evaluation</li>
<li>A demonstrated product mindset, with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback</li>
<li>High ownership and bias for action in 0-to-1 environments: comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption</li></ul> 
Nice to have:
<ul><li>Experience in martech, ideally a go-to-market or business use case with an analytical (rather than purely transactional) angle</li>
<li>An academic or research background that can help us innovate and develop novel methods</li></ul> 
<div><div><div>Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. 
 
</div><div>Local Pay Range</div>
<div>$192,000&mdash;$260,000 USD
</div></div></div><div>About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide &mdash; including Comcast, Cond&eacute; Nast, Grammarly, and over 50% of the Fortune 500 &mdash; rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark&trade;, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
 
 
Benefits
 
 
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. 
 
 
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</div></div>

Staff Software Engineer - AI/ML

NYU Langone Health

<div>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.
 
 
For more information, go to med.nyu.edu, and interact with us on LinkedIn, Glassdoor, Indeed, Facebook, Twitter and Instagram.

Position Summary: 
We have an exciting opportunity to join our team as a Engineer II - Applied AI.
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).

Job Responsibilities:
<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> 

Minimum Qualifications: 
To qualify you must have a 1. Bachelor's degree in computer science, software engineering, or a related field. 
2. At least 1-3 years of hands-on experience in AI Solution development 
3. Strong programming skills in Python, or other languages commonly used in AI development. 
4. Substantial knowledge of AI, machine learning, and deep learning 
5. Experience with AI platforms like PyTorch or TensorFlow 
6. Experience with building large-scale and/or compute-intensive applications on clusters for data engineering, model training and evaluation (HPC, Spark, Kubernetes) 
7. Understanding of software development principles and methodologies, including data structures, data modeling and software architecture. 
8. Excellent problem-solving skills and ability to work in a team environment. 
9. Excellent communication skills, both verbal and written.

Preferred Qualifications: 
1. Masters degree in computer science, data science, software engineering, or a related quantitative discipline 
2. 3-5 years of hands-on experience in AI Solution development 
3. Basic understanding of at least one cloud (Azure, AWS, GCP) and cloud native development tools, and experience using their AI / ML toolchain

Qualified candidates must be able to effectively communicate with all levels of the organization.
 
 
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.
 
 
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.
 
 
View Know Your Rights: Workplace discrimination is illegal.

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.

To view the Pay Transparency Notice, please click here</div>

Machine Learning Engineer

Cloaked

<div>Cloaked is a consumer privacy and identity platform on a mission to give people back control of their personal data. We let anyone generate unlimited identities - masked emails, phone numbers, and payment cards - scrub their information off data-broker sites, and shield themselves from spam, scams, and breaches, all from one app. Backed by a $375M Series B, we've protected 10M+ identities and removed 1B+ records from the data brokers who profit off personal information. Now we're building the AI-native future of privacy: autonomous agents that monitor, manage, and defend your digital footprint for you.
ABOUT THE ROLE
We're looking for a Senior Software Engineer, AI to lead the development and strategic direction of Cloaked's AI Agents - autonomous agents that act on a user's behalf to monitor, manage, and enforce their privacy across their entire digital footprint. They find where your data is exposed, take action to remove it, and continuously defend your privacy in the background - turning what's always been a manual, reactive chore into something automated and continuous. 1B+ records removed to date, and now we're automating the entire fight. 
 
You'll own the technical roadmap end-to-end: agent architecture and orchestration, tool-use and integrations across third-party services, reliability and guardrails for non-deterministic systems, adversarial robustness against hostile web content, and the cloud infrastructure underneath. Long-term, this role grows beyond Agents. You'll contribute across Cloaked's engineering org and help shape how we build AI-native consumer products at scale.
WHAT WILL YOU DO?<ul><li>
Lead the technical roadmap and architecture for Cloaked's AI agent platform</li><li>
Design and build production agents that monitor, manage, and enforce users' privacy across their digital footprint autonomously</li><li>
Build agents that take real action on users' behalf - submitting data-removal requests, navigating opt-out flows, and adjusting privacy settings across hundreds of services</li><li>
Build defenses for adversarial environments, including prompt injection, untrusted web content, and hostile data sources</li><li>
Integrate and evaluate frontier models (LLMs, agent frameworks, tool-use) for production use</li><li>
Own the orchestration layer, integrations, and the cloud infrastructure the agents run on</li><li>
Collaborate with design, mobile, and product teams to ship agent experiences that feel effortless to end users</li><li>
Serve as the AI agents domain expert on the team, raising the engineering bar through code reviews, architecture discussions, and mentorship</li><li>
Help the team ship features faster and with fewer bugs by setting the technical standard for the product</li><li>
Actively leverage AI tools in day-to-day engineering work</li><li>
Contribute across engineering teams beyond Agents as the business scales</li></ul>
WHAT SKILLS AND EXPERIENCES WILL HELP YOU?<ul><li>
Strong software engineering fundamentals - production systems, distributed systems, real-time infrastructure</li><li>
Hands-on experience building agentic or LLM-powered products in production</li><li>
Proficiency with modern agent stacks: LLM orchestration and agent frameworks (LangGraph, LangChain, LlamaIndex, or similar), tool-use/function calling, and RAG</li><li>
Deep familiarity with LLMs, evals, and prompt engineering in production environments</li><li>
Experience building reliability and guardrails into non-deterministic systems</li><li>
Proficiency in Python and/or Go, with a track record of building scalable backend systems</li><li>
Experience designing and deploying secure, production-grade APIs</li><li>
Strong understanding of cloud infrastructure (AWS, GCP) and containerized deployments</li><li>
Track record shipping consumer products at scale</li><li>
Active daily use of AI coding tools (Cursor, Claude, Codex) with strong prompt judgment and tool selection instincts</li></ul>
WHAT'S NICE TO HAVE?<ul><li>
Experience with browser automation, headless automation, or web scraping at scale</li><li>
Background in agent observability, eval frameworks, or LLMOps</li><li>
Familiarity with adversarial ML, AI safety, prompt-injection defense, or anti-fraud system design</li><li>
PII handling and sensitive data awareness</li><li>
Prior exposure to consumer privacy or security-focused products</li><li>
Experience with workflow orchestration and job scheduling at scale</li></ul>
WHAT DO WE LIKE?<ul><li>
Passion for security, privacy, and internet ethics</li><li>
Curiosity and constant learning at the frontier of agentic AI and applied ML</li><li>
Strong analytical thinking with proactive problem-solving abilities</li><li>
Ownership mentality - comfortable holding the pen on technical direction</li><li>
Effective team player in high-velocity environments</li><li>
Comfortable mentoring and knowledge sharing across teams</li><li>
Experience in startups or growth-stage companies</li><li>
Interest in data tracking, analytics, and product instrumentation</li></ul><h2 class="jobSectionHeader">
What We Offer</h2>
Cloaked is a well-funded Series B startup based out of NYC.
Although we are a distributed team, the NYC team operates with a hybrid model. The office building is home to several amenities, including a gourmet cafe, cocktail bar, and a rooftop work area.
We have a fully built out kitchen packed with drinks and snacks. The Cloaked team has diverse interests and so we frequently embark on team outings and go out for socials!<div> 
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Compensation and Benefits</h2>
We offer above market rate pay and equity based off of the market&rsquo;s best commercially available data. Your compensation will be a combination of salary, bonus and equity.
Cloaked employees have 401K, as well as top of the line Health, Dental, and Vision benefits.
We offer flexible work arrangements and the ability to work remotely as needed. Cloaked provides a home office stipend in addition to a new company laptop (and other tech depending on the role).<div> 
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Perks</h2>
Competitive PTO: We encourage employees to take a minimum # of vacation per quarter. We see PTO as a preventative burnout measure and are committed to changing the industry standard.
Monthly health stipend: Used for any kind of physical, mental or emotional care you&rsquo;d like to take for yourself, be it a gym membership, a meditation app, or time with a personal trainer.
Late Night Meals: We understand that sometimes work can get in the way of meal prep. In response to that, we offer employees a monthly meal stipend to be used when they don&rsquo;t have time to get a home cooked meal going!
Professional Growth: Opportunities for career development and personal growth are provided to all employees who seek to further their knowledge and capabilities through an unlimited professional development fund. Additionally team members are encouraged to regularly attend conferences and industry events.
We are really excited about having you join our mission-driven team and help us build the future of online privacy!<div></div> 
Compensation Range: $180K - $250K</div>

Senior Software Engineer, AI

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