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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> 
</div><h2 class="jobSectionHeader">
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> 
</div><h2 class="jobSectionHeader">
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

Cohere

<div>
 
 Who are we?
 
 
 
 Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
 
 
 We&rsquo;re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
 
 
 We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!
 
 
 
 Why this role?
 
 
 
 We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics &amp; Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line.
 
 
 
 As a Data Engineer, You Will
 
 
 
 <ul>
 <li>
 Work directly on new customer experiences built on one of the most advanced AI systems in the world
 </li>
 <li>
 Collaborate daily with researchers and engineers who are some of the best in the world at what they do
 </li>
 <li>
 Run implementations end-to-end and see initiatives through to real outcomes
 </li>
 <li>
 Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 5+ years of experience working on production-grade data processing systems
 </li>
 <li>
 Strong command of Python and SQL
 </li>
 <li>
 Experience with distributed data processing frameworks such as Apache Beam, Spark, or Flink, alongside large-scale data system design
 </li>
 <li>
 The ability to transform unstructured data into performant datasets in relational databases and blob storage
 </li>
 <li>
 Familiarity with modern analytics stack tooling such as BigQuery, Airflow, or dbt
 </li>
 <li>
 Knowledge of Java or Golang (nice to have)
 </li>
 <li>
 Experience with Kubernetes (nice to have)
 </li>
 <li>
 Genuine excitement about AI - you follow the research, have opinions, and enjoy being in the weeds
 </li>
 <li>
 Comfort operating at the edge of what's known, with a desire to build something genuinely new rather than optimise what already exists
 
 
 </li>
 </ul>
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 <ul>
 <li>
 A weekly lunch stipend of $75/&pound;75 or equivalent in your local currency for lunch.
 </li>
 <li>
 Full health and dental benefits, including a separate budget for mental health.
 </li>
 <li>
 RRSP matching, 401K, Pension Scheme.
 </li>
 <li>
 100% Parental Leave top-up for up to 6 months, for either parent.
 </li>
 <li>
 Annual enrichment benefits:
 
 
 </li>
 </ul>
 Arts &amp; culture, fitness/wellness, quality time, and a workspace improvement credit.
 
 
 Education &amp; learning stipend for conferences, courses, and coaching.
 
 
 <ul>
 <li>
 6 weeks of paid vacation (30 working days!)
 </li>
 <li>
 Budget for traveling to other offices if you are remote, plus an annual company offsite.
 
 
 </li>
 </ul>
 
 How And Where We Work
 
 
 
 <ul>
 <li>
 Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
 </li>
 <li>
 For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
 </li>
 <li>
 For those not near an office: a co-working benefit so you can work alongside others in your city.
 </li>
 <li>
 Everyone receives a $500 home office stipend to set up your workspace properly.
 
 
 </li>
 </ul>
 If any of the above doesn&rsquo;t line up exactly with your experience, we still encourage you to apply.
 
 
 We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
</div>

Data Engineer, Data Foundations

Turing

<div>
 
 
 About Turing
 
 
 
 Based in San Francisco, California, Turing is the world&rsquo;s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&amp;L.
 
 
 
 
 
 
 Role Overview
 
 
 
 Turing is looking for Venture Capital professionals to work with our researchers to improve the performance of AI models. You will apply your expertise in startup evaluation, funding rounds, cap table management, and early-stage market analysis to evaluate and train AI systems. If you enjoy solving complex problems in venture capital and are interested in shaping the future of AI in finance, please apply. No prior AI experience is required.
 
 
 
 
 
 
 What Does Day-to-Day Look Like
 
 
 <ul>
 <li>
 Evaluate LLM models on venture capital topics such as startup valuation, term sheet analysis, cap table modeling, and market sizing.
 </li>
 <li>
 Create rubrics to assess model capabilities on tasks like due diligence for early-stage companies, funding round structuring, and portfolio construction for VC funds.
 </li>
 <li>
 Collaborate with AI researchers and fellow finance experts to shape training methods, evaluation strategies, and benchmarks.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 2+ years of experience in Venture Capital (e.g., seed/Series A&ndash;C investing, VC fund operations, or startup advisory).
 </li>
 <li>
 Strong grasp of startup valuation methods, term sheet negotiation, cap table mechanics, and venture fund economics.
 </li>
 <li>
 Excellent English written communication.
 </li>
 </ul>
 
 
 
 
 
 Bonuses (Not at All Necessary)
 
 
 <ul>
 <li>
 CFA (Level I/II/III), MBA in Finance, or operational experience at a high-growth startup.
 </li>
 </ul>
 
 
 
 
 
 Perks of Freelancing with Turing
 
 
 <ul>
 <li>
 Work on the cutting edge of AI and finance.
 </li>
 <li>
 Fully remote and flexible work environment.
 </li>
 <li>
 Competitive hourly compensation of ~$100+/hour depending on experience.
 </li>
 </ul>
 
 
 
 
 
 Offer Details
 
 
 <ul>
 <li>
 Commitment: Flexible, 10&ndash;30 hrs/week.
 </li>
 <li>
 Duration: ~1 month, with the possibility of extension based on performance and project needs.
 </li>
 </ul>
 
 
 
 
 
 After applying, you&rsquo;ll receive a login link by email. Please complete your profile promptly so we can proceed with your application.
 
 
 
 
 
 
 
 We&rsquo;re actively hiring for this role. If you know exceptional talent, please refer them at
 
 turing.com/referrals
 
 and earn money for successful referrals.
 
 
</div>

Remote Venture Capital Analyst ($100/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
 
 
 qUN1H2divA
</div>

Machine Learning Engineer / Data Scientist

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

Coinbase

<div>
 
 Ready to do the most impactful work of your career? At&nbsp;Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it&rsquo;s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called &ldquo;surges.&rdquo;&nbsp;learn more about working at Coinbase.
 
 
 As a Prime Sales Trader on the Institutional Prime Trading team, you'll help grow one of Coinbase's most strategically important businesses by delivering best-in-class execution and liquidity solutions to the world's most sophisticated institutional clients. Our clients include asset managers, hedge funds, VCs, family offices, pensions, and endowments across both crypto-native and traditional finance. You'll drive trading volume, deepen counterparty relationships, and shape how institutional clients experience Coinbase's execution services across spot and derivatives markets.
 
 
 
 What you'll do:
 
 
 <ul>
 <li>
 Drive increased trading volume by understanding clients' liquidity needs, proactively identifying how high-touch and low-touch execution services can meet those needs, and providing real-time support for execution and market color.
 </li>
 <li>
 Build and maintain trusted counterparty relationships through quality execution, daily market updates on liquidity and flow thematics, and consistent, high-quality service delivery.
 </li>
 <li>
 Partner with Sales, Financing, and Account Management teams to identify, onboard, and monetize new client relationships, proactively surfacing business opportunities across Coinbase's institutional product suite.
 </li>
 <li>
 Provide structured feedback from clients and the broader marketplace to institutional Product Managers, guiding new product development across spot trading and financing.
 </li>
 <li>
 Maintain a real-time pulse on market sentiment, trading activity, and client positioning, keeping relevant internal teams informed to support strategic decision-making.
 </li>
 </ul>
 
 
 Required Skills and Experience:
 
 
 <ul>
 <li>
 3+ years of sales and/or trading experience in digital assets, FX, equities, credit, or derivatives at a top-tier institution, with direct experience in daily execution and settlement functions.
 </li>
 <li>
 Strong options trading capability, including pricing, hedging, and risk-managing vanilla and/or exotic structures, with fluency in Greeks, volatility dynamics, and options market microstructure.
 </li>
 <li>
 Proven ability to build and maintain counterparty relationships with institutional clients, translating market insight into trusted, high-value interactions.
 </li>
 <li>
 Experience producing institutional-grade market commentary or client communications covering macro, crypto, or digital asset themes.
 </li>
 <li>
 Weekend availability required - this role operates on a schedule that includes Saturday and Sunday as working days.
 </li>
 <li>
 Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
 </li>
 </ul>
 
 
 PID:
 
 P77366
 
 
 Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)).&nbsp;&nbsp;
 
 
 Annual base salary range (excluding equity and bonus):: $157,590 USD - $185,400 USD
 
 <ul>
 <li>
 
 
 Application Limit:
 
 
 Candidates may submit a maximum of 3 applications within a 6-month period.
 </li>
 <li>
 
 
 
 Equal Opportunity Employer:
 
 Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws.
 
 
 </li>
 <li>
 
 
 
 US Applicants:
 
 View Employee Rights, Know Your Rights, and E-Verify Notice of Participation.
 
 
 </li>
 <li>
 
 
 
 Accommodations:
 
 If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com.&nbsp;Need screen reading technology? Click here to download a free compatible screen reader and view the
 
 
 tutorial.
 
 
 </li>
 <li>
 
 
 
 Data Privacy &amp; Arbitration:
 
 By submitting your application, you agree to our Candidate Privacy Notice. US applicants: By submitting your application, you agree to Arbitration of Disputes.
 
 
 
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 <li>
 
 
 
 AI Disclosure:
 
 Coinbase is piloting an AI tool based on machine learning technologies to conduct initial screening interviews to qualified applicants. The tool simulates realistic interview scenarios and engages in dynamic conversation.&nbsp; Coinbase is also piloting an AI interview intelligence platform to transcribe and summarize interview notes, allowing our interviewers to fully focus on you as the candidate. Coinbase will not use AI to make decisions impacting employment.
 
 
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 </ul>
</div>

Prime Sales Trader

Ethos

<div>
 
 
 Note: This is a flexible, remote, part-time opportunity that is 5-20 hours per week at $100 per hour (up to $2k/week).
 
 
 
 
 
 
 We're working with a leading foundational AI lab to find experienced nurse practitioners who can help train their latest language model on advanced practice nursing and clinical assessment tasks.
 
 
 
 
 
 We're looking for NPs with 5+ years of independent practice in primary care or specialty settings to create, evaluate, and refine AI-generated work across core NP workflows: patient history and physical documentation, differential diagnosis notes, treatment planning, prescribing rationale, patient education materials, and clinical decision memos.
 
 
 
 
 
 
 Compensation:
 
 $100/hour
 
 
 
 Commitment:
 
 Flexible, up to 20 hours per week (up to $2k/week)
 
 
 
 Location:
 
 Fully remote, work on your own schedule
 
 
 
 Start date:
 
 April
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 Certified Nurse Practitioner with 5+ years of advanced practice experience
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 Strong clinical expertise in diagnosis, treatment planning, and patient management
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 Excellent written communication and attention to detail
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 </ul>
 
 
 
 
 
 About Ethos
 
 
 
 Ethos is a new expert network built by a McKinsey/SoftBank/DeepMind team and backed by world-leading investors like General Catalyst. We connect experts with investors and consultancies for paid expert calls, speaking engagements, and advisory opportunities.
 
</div>

Senior Nurse Practitioner ($100/hr, up to $2,000/week)

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