freelance data scraping engineer (python)

software engineer

data engineer

ai engineer

data platform engineer (python) Jobs in New York

data platform engineer (python)

freelance data scraping engineer (python) Jobs in New York

python engineer

Alignerr

<div>
 
 About The Role
 
 
 
 What if your Python expertise could directly shape the infrastructure powering next-generation AI? We're looking for a Senior Python Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve their models.
 
 
 This is a fully remote contract role working on real production systems &mdash; not toy projects. You'll be embedded alongside data, research, and engineering teams doing meaningful, high-visibility work at the frontier of AI development.
 
 
 <ul>
 <li>
 Organization: Alignerr
 </li>
 <li>
 Type: Hourly Contract
 </li>
 <li>
 Location: Remote
 </li>
 <li>
 Commitment: 20&ndash;40 hours/week
 
 
 </li>
 </ul>
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and evaluation workflows
 </li>
 <li>
 Develop full-stack tooling and backend services for data annotation, validation, and quality control
 </li>
 <li>
 Identify and fix bottlenecks, edge cases, and reliability issues across production Python codebases
 </li>
 <li>
 Collaborate directly with data, research, and engineering teams to support model training and benchmarking
 </li>
 <li>
 Participate in synchronous design reviews to iterate on architecture and implementation decisions
 </li>
 <li>
 Improve performance, safety, and scalability across existing infrastructure
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Native or fluent English speaker with clear written and verbal communication skills
 </li>
 <li>
 5+ years of professional experience writing production-grade Python for data engineering
 </li>
 <li>
 Strong full-stack developer background with solid systems programming fundamentals
 </li>
 <li>
 Proficient with workflow orchestration tools for managing complex dependency graphs
 </li>
 <li>
 Experienced with dataframe processing libraries and cloud data warehouse SDKs
 </li>
 <li>
 Able to commit reliably to 20&ndash;40 hours per week
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Prior experience with data annotation, data quality pipelines, or evaluation systems
 </li>
 <li>
 Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
 </li>
 <li>
 Experience with distributed systems or developer tooling
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects alongside leading research labs at the frontier of the field
 </li>
 <li>
 Fully remote and flexible &mdash; work from wherever you do your best thinking
 </li>
 <li>
 Freelance autonomy with the structure and consistency of meaningful, ongoing technical work
 </li>
 <li>
 Make a direct, tangible impact on the systems that shape how AI models learn and improve
 </li>
 <li>
 Potential for extended engagement and expanded scope as projects evolve
 </li>
 </ul>
</div>

Data Platform Engineer (Python)

James Search Group

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

Machine Learning Engineer

Catalyst Labs

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

ML Engineer

Mindrift

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

Freelance Machine Learning Engineer

Bisnow

<div>
 
 
 We&rsquo;re hiring an entry-level AI Engineer to help our company get more value out of AI every day. This is a new, hands-on role for someone genuinely excited about AI&mdash;not someone with a decade of ML experience. You&rsquo;ll be on the front lines of applying AI in a real business: building Claude skills, writing programs with Claude Code, and creating practical tools and workflows that improve how teams work every day.
 
 
 
 
 
 
 This is a rare opportunity to grow into an AI career from the ground floor. You don&rsquo;t need prior professional experience&mdash;what matters is curiosity, clear thinking, a willingness to experiment, and strong written communication. If you&rsquo;ve been teaching yourself tools like Claude, ChatGPT, or Cursor through side projects or automations, you&rsquo;ll fit right in.
 
 
 
 
 
 
 You&rsquo;ll work closely with the CTO and engineering leadership, partner across teams like Editorial, Sales, Marketing, Events, and Operations, and help identify where AI can remove toil and create real leverage&mdash;all while learning, experimenting, and shipping solutions that actually get used.
 
 
 
 
 
 Bisnow Overview
 
 
 
 Bisnow is the leading B2B media platform powering the commercial real estate industry. We connect CRE professionals through award-winning news, high-impact events, marketing solutions, recruiting services, and sales enablement tools that drive real business results.
 
 
 With 1.7M+ subscribers and 400+ events annually across 47 markets in the U.S., Canada, the UK, Ireland, and the Netherlands, we don&rsquo;t just cover the industry, we help move it forward.
 
 
 We inform. We connect. We create opportunities that turn into deals. Global mindset. Hyper-local execution.
 
 
 
 Key Responsibilities
 
 
 
 
 
 Build Claude Skills for the Company
 
 
 
 
 <ul>
 <li>
 Design, write, and maintain Claude skills (SKILL.md files with YAML frontmatter and supporting scripts) that encode repeatable workflows our teams use every day.
 </li>
 <li>
 Interview stakeholders across the business to identify tasks worth turning into skills &mdash; from editorial workflows to sales outreach to data pulls.
 </li>
 <li>
 Follow skill authoring best practices: clear when-to-use descriptions, progressive disclosure, bundled reference files, and embedded scripts when needed.
 </li>
 <li>
 Test, evaluate, and iterate on skills &mdash; measure whether they actually improve outputs versus a baseline prompt, and tune accordingly.
 </li>
 <li>
 Maintain a central, documented skill library with versioning and clear usage guidance.
 
 
 
 </li>
 </ul>
 
 
 Build Programs with Claude Code
 
 
 
 
 <ul>
 <li>
 Use Claude Code as a daily collaborator to build internal tools, automations, scripts, and small applications.
 </li>
 <li>
 Write AGENTS.md and CLAUDE.md files that teach agents our coding standards, repo structure, and team conventions.
 </li>
 <li>
 Develop agentic workflows that combine Claude Code with MCP (Model Context Protocol) servers for Salesforce, Google Workspace, Slack, GitHub, and internal systems.
 </li>
 <li>
 Apply the Plan / Execute / Review loop &mdash; decompose work into scoped tasks, run them through agents, review carefully, and ship.
 </li>
 <li>
 Ship real code: pull requests, tests, documentation, deployment &mdash; working alongside senior engineers for mentorship and code review.
 
 
 
 </li>
 </ul>
 
 
 Enable AI Adoption Across the Company
 
 
 
 
 <ul>
 <li>
 Be the internal go-to person for "how do I get Claude to help me with this?"
 </li>
 <li>
 Run training sessions, office hours, and hands-on workshops for non-technical teams on prompting, Claude Projects, skills, and agent use.
 </li>
 <li>
 Write and maintain internal documentation: prompt libraries, skill directories, how-to guides, and best-practice playbooks.
 </li>
 <li>
 Partner with team leads to identify high-value AI use cases in Editorial, Sales, Marketing, Events, Finance, and Operations &mdash; then prototype solutions.
 </li>
 <li>
 Stay current on AI product releases (Claude, Claude Code, MCP ecosystem, browser agents, etc.) and translate what matters into actionable recommendations for the business.
 
 
 
 </li>
 </ul>
 
 
 Prototype and Evaluate AI Features
 
 
 
 
 <ul>
 <li>
 Build quick proofs-of-concept using the Anthropic API &mdash; Python, JavaScript, or whatever fits.
 </li>
 <li>
 Design and run evaluations: what does "good" output look like, what percentage of the time does the workflow succeed, and what happens in the failure cases?
 </li>
 <li>
 Think probabilistically. AI features are not deterministic, and part of your job is designing around that reality.
 </li>
 <li>
 Integrate AI workflows with existing systems via MCP connectors, simple APIs, and light glue code.
 
 
 
 </li>
 </ul>
 
 
 Collaborate and Document
 
 
 
 
 <ul>
 <li>
 Write clearly &mdash; in Slack, in docs, in skill descriptions, in PR comments. Written communication is central to this role.
 </li>
 <li>
 Demo your work frequently, gather feedback, and iterate.
 </li>
 <li>
 Contribute to internal AI policy and responsible-use guidelines.
 
 
 
 </li>
 </ul>
 
 
 Our AI Stack
 
 
 
 
 <ul>
 <li>
 Core AI Platform: Claude (claude.ai, Claude Projects, Claude Code), Anthropic API
 </li>
 <li>
 Skills &amp; Agents: Claude skills (SKILL.md), subagents, MCP servers, Claude in Chrome
 </li>
 <li>
 Integrations: Salesforce, Google Workspace (Drive, Gmail, Calendar), Slack, GitHub, n8n
 </li>
 <li>
 Languages: Python and JavaScript/TypeScript (you should be comfortable reading and writing basic code in at least one)
 </li>
 <li>
 Supporting Stack: PHP/Laravel, AWS, Redshift/MySQL/PostgreSQL, Docker &mdash; you are not expected to know these on day one, but exposure will come quickly
 </li>
 <li>
 Dev Environment: macOS, VS Code, Git/GitHub, Claude Code CLI
 
 
 
 </li>
 </ul>
 
 What are we looking for?
 
 
 
 
 Required
 
 
 
 <ul>
 <li>
 Genuine, demonstrable enthusiasm for AI. Tell us what you have built, broken, or experimented with &mdash; side projects, automations, Claude Projects, custom GPTs, hobbyist scripts, anything.
 </li>
 <li>
 Strong written communication. You can explain a technical concept in plain English and craft clear, specific prompts.
 </li>
 <li>
 Comfort with basic programming. You can read and write simple Python or JavaScript, use the command line, and work with Git.
 </li>
 <li>
 Structured thinking. You can break a messy problem into steps and describe each one clearly &mdash; this is the core skill behind both prompting and skill authoring.
 </li>
 <li>
 Willingness to work in public. You ask questions in Slack, demo rough drafts, and share what you learn.
 </li>
 <li>
 Curiosity and self-direction. When you hit something you do not know, your first instinct is to go figure it out &mdash; often with Claude as your study partner.
 </li>
 <li>
 Attention to detail. Small changes in prompts, skill descriptions, and instructions matter a lot.
 
 
 
 </li>
 </ul>
 
 
 Nice to Have (none of these are required)
 
 
 
 
 <ul>
 <li>
 A portfolio of AI experiments &mdash; custom GPTs, Claude skills or Projects, agent workflows, Discord/Slack bots, browser automations, etc.
 </li>
 <li>
 Experience using Claude Code, Cursor, GitHub Copilot, or another AI coding assistant on a real project.
 </li>
 <li>
 Familiarity with APIs and JSON &mdash; making a REST call, parsing a response.
 </li>
 <li>
 Exposure to SQL. We live in Redshift and will teach you, but any prior SQL helps.
 </li>
 <li>
 Experience writing technical documentation, tutorials, or how-to content.
 </li>
 <li>
 A background in teaching, training, customer support, or writing &mdash; anyone who has explained technical ideas to non-technical people.
 </li>
 <li>
 Awareness of the MCP ecosystem or agent frameworks.
 </li>
 <li>
 A degree in a technical field is welcome but not required &mdash; we hire based on skills, not credentials.
 
 
 
 </li>
 </ul>
 
 What's in it for you?
 
 
 
 <ul>
 <li>
 Competitive compensation structure!
 </li>
 <li>
 Medical, Dental and Vision Insurance - effective the 1st of the month following your start date
 </li>
 <li>
 Short and Long Term Disability Insurance - this includes maternity and paternity leaves as well.
 </li>
 <li>
 401K Profit Sharing Plan
 </li>
 <li>
 Flexible Spending Account
 </li>
 <li>
 Health Savings Account
 </li>
 <li>
 Dependent Care Account
 </li>
 <li>
 Unlimited Vacation Days
 </li>
 <li>
 7 days paid sick leave
 </li>
 <li>
 9 paid Holidays
 </li>
 <li>
 Referral Bonus Program
 </li>
 <li>
 Pet Friendly Offices
 </li>
 <li>
 You&rsquo;ll get to work with incredibly smart, passionate, driven, ambitious, kind, caring and mindful people and will rarely experience an overload of policies, bureaucracy or toxicity (the latter, we do not tolerate)
 
 
 
 </li>
 </ul>
 Before applying, please read our values below. Our values describe and give insight into our culture. If you do not share the same values, this role will not be a mutually beneficial fit. If you do share these values and want to apply, we encourage you to do so.
 
 
 
 
 Our values demand that we be curious, self-aware, fearless, consistent. We say yes to seemingly insurmountable challenges because we dare ourselves to push further. And we go the distance because we are individually and collectively entrepreneurial, always asking: Why can&rsquo;t it be done? We find a way because we care more than the competition. We embrace team and disown ego. We are ruthlessly disciplined and unabashedly kind. We unreservedly challenge the status quo and vigorously fight for new levels of excellence. We believe the difference between good and great is exceptional communication. We obsess over creating value for our team and our customers. We push ourselves and our industry to be more inclusive, to champion diversity and to fight racism, gender bias and all forms of inequality. We never peak. We never quit. We never have excuses. We own our failures and we commit to being smarter and stronger because of them. We give our best today and even better tomorrow. We are here to win.
 
 
 
 
 Bisnow will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require Bisnow's sponsorship to continue to work legally in the United States.
 
 
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
 
 
 Get To Know Our Teams! &lt; Click here for more info about Bisnow, Biscred &amp; SelectLeaders!
</div>

AI Engineer

ReadMe

<div>
 
 📍 Locations: San Francisco (Hybrid), New York (Hybrid), Columbus (Hybrid), or Remote (US)
 
 
 
 We&rsquo;re hiring an AI Engineer to shape how AI shows up across ReadMe&rsquo;s product: from how developers explore and understand APIs to how companies author and maintain their documentation.
 
 
 We&rsquo;re at the forefront of a major shift in developer experience:
 
 
 <ul>
 <li>
 AI agents need APIs to talk to each other, and those APIs need to be understandable, structured, and explorable
 </li>
 <li>
 At the same time, writers and developers are looking for better ways to generate and maintain documentation with AI
 
 
 </li>
 </ul>
 We're a small team of humans (and one owl) working together to do big things &mdash; and that&rsquo;s where you come in. In this role you&rsquo;ll have a transformational impact on ReadMe across both the trajectory of the business and our thriving culture.
 
 
 🦉 What we do
 
 
 ReadMe helps more than 5,000 leading startups and tech companies build beautiful, personalized, and interactive developer hubs. If you&rsquo;ve ever visited the developer docs for PagerDuty, Samsara, or Nvidia, you&rsquo;ve used ReadMe!
 
 
 We love what we do because it&rsquo;s so much more than just documentation. We&rsquo;re providing tools for teams to build a better developer experience and make their products and APIs easier to use. We&rsquo;ve got great support from our investors at Accel who led our Series A, and our interview process reflects the open, caring, and whimsical culture we want to maintain as we scale.
 
 
 ✅ What you&rsquo;ll do here
 
 
 This isn&rsquo;t a feature team where a PM hands you tickets. You&rsquo;ll help decide what gets built, why it matters, and how it works end-to-end. You&rsquo;ll work on systems that are already live across thousands of developer hubs and define what they become next.
 
 
 ReadMe's AI surface spans three bets we're doubling down on:
 
 
 <ul>
 <li>
 Documentation that writes itself. AI that watches code change and keeps docs current &mdash; from PR-level suggestions to org-wide audits that surface and fix quality issues at scale.
 </li>
 <li>
 Answers, not search results. A conversational layer embedded directly in developer hubs, grounded in real docs, that gives developers the right answer instead of a list of links to dig through.
 </li>
 <li>
 APIs that are agent-ready. As AI agents increasingly talk to APIs, the structure and clarity of those specs matters more than ever. We're building the systems that make APIs understandable by both humans and machines.
 
 
 </li>
 </ul>
 Day to day, you&rsquo;ll:
 
 
 <ul>
 <li>
 Design end-to-end AI systems: combining LLMs, embeddings, retrieval pipelines, and structured outputs into reliable product features.
 </li>
 <li>
 Build grounding and retrieval layers: indexing docs, OpenAPI specs, and customer data to support accurate, context-aware generation.
 </li>
 <li>
 Define evaluation systems: measuring accuracy, latency, cost, and user impact; building feedback loops to continuously improve quality.
 </li>
 <li>
 Handle real-world complexity: malformed specs, inconsistent docs, edge-case APIs, and ambiguous user queries.
 </li>
 <li>
 Make architectural tradeoffs: latency vs. quality, cost vs. coverage, deterministic vs. generative approaches.
 </li>
 <li>
 Own production reliability: observability, fallbacks, rate limiting, and safe degradation when systems fail.
 </li>
 <li>
 Work across the stack: from model orchestration and backend systems to the UI surfaces that expose them.
 
 
 </li>
 </ul>
 💙 You'll love this job if you...
 
 
 <ul>
 <li>
 Want to own meaningful systems end-to-end, not just features.
 </li>
 <li>
 Care deeply about developer experience and documentation quality.
 </li>
 <li>
 Enjoy working on problems where AI, APIs, and product design intersect.
 </li>
 <li>
 Have strong instincts about what makes AI actually useful and where the industry is headed.
 
 
 </li>
 </ul>
 ️ ⭐️ This role is a great fit if you have...
 
 
 <ul>
 <li>
 Experience building with LLMs in production, not just prototypes.
 </li>
 <li>
 Strong JavaScript/TypeScript or Python experience.
 </li>
 <li>
 Experience working with:
 </li>
 <ul>
 <li>
 Embeddings and retrieval systems (RAG).
 </li>
 <li>
 Prompting and structured outputs.
 </li>
 <li>
 Evaluation and iteration of AI systems (quality, latency, cost).
 </li>
 </ul>
 <li>
 Comfort working with APIs and structured data (JSON, OpenAPI, schemas).
 </li>
 <li>
 Experience designing and shipping end-to-end systems, from backend pipelines to user-facing product surfaces.
 </li>
 <li>
 Strong instincts around when to use AI vs. deterministic approaches.
 </li>
 <li>
 Experience improving AI reliability, observability, and production readiness.
 </li>
 <li>
 Familiarity with real-world edge cases (messy data, inconsistent inputs, ambiguous queries) and how to handle them.
 
 
 </li>
 </ul>
 🌱 How you'll grow within one month...
 
 
 <ul>
 <li>
 Build a deep understanding of ReadMe&rsquo;s AI systems and product surfaces.
 </li>
 <li>
 Ship meaningful improvements to existing AI features.
 </li>
 <li>
 Get close to real customer workflows and pain points.
 
 
 </li>
 </ul>
 🪴 Within a few months, you'll...
 
 
 <ul>
 <li>
 Own a core part of one of our AI systems.
 </li>
 <li>
 Drive improvements in quality, reliability, and user experience.
 </li>
 <li>
 Contribute to product and technical direction.
 
 
 </li>
 </ul>
 🌳 Within your first year, you'll...
 
 
 <ul>
 <li>
 Be a key driver of AI across the product.
 </li>
 <li>
 Ship systems used daily by thousands of developers and teams.
 </li>
 <li>
 Help define how AI reshapes developer hubs and API workflows.
 
 
 </li>
 </ul>
 🛣️ What's the hiring process like?
 
 
 <ul>
 <li>
 We can&rsquo;t wait to read your resume and (hopefully personality-filled) cover letter! Let us know what excites you about full stack engineering, and help us get to know you better!
 </li>
 <li>
 If we think we might be a good fit for you, we&rsquo;ll set up a 30 minute phone chat with our VP Engineering Moses! He&rsquo;ll tell you more about the role, and get a chance to hear about your experiences.
 </li>
 <li>
 Next will be a second 30 minute phone interview with Davin, one of our Engineering Managers, where we&rsquo;ll dive a bit more into your background.
 </li>
 <li>
 We&rsquo;ll then do a technical assessment with a couple of ReadMe engineers.
 </li>
 <li>
 Finally we&rsquo;ll invite you to an "onsite" interview conducted over Zoom! These usually take 3.5 to 5 hours including an hour break in between. We are able to be flexible with the schedule and split it up over two days if that works best for you! We start with a 15-minute get-to-know-you with the people you&rsquo;ll be interviewing with, and then have you talk with people one-on-one later on.
 </li>
 <li>
 We&rsquo;ll let you know how things went within a week! If it still seems like a good fit all around, we&rsquo;ll extend you an offer! If not, we will update you to let you know so you aren&rsquo;t left hanging.
 
 
 </li>
 </ul>
 
 ✨ Our Benefits Include&hellip;
 
 
 
 <ul>
 <li>
 Unlimited PTO with a three-week minimum. 🏝️
 </li>
 <li>
 Fully covered medical, dental, and vision insurance for you, and 100% for your dependents.
 </li>
 <li>
 A One Medical membership. 👨&zwj;⚕️
 </li>
 <li>
 A gym or fitness stipend of up to $150 per month. 🏋️&zwj;&female;️
 </li>
 <li>
 One-to-one donation matching of up to $1,000 per year. 💸
 </li>
 <li>
 Twelve weeks of paid parental leave after the birth or adoption of a child. 🐣
 </li>
 <li>
 Work from home. 🏠
 </li>
 <li>
 Three offsite retreats per year to get together with coworkers and plan for the quarter ahead. ✈️
 </li>
 <li>
 Take a look at our handbook for more information on our benefits! 📘
 
 
 </li>
 </ul>
 Not sure if you&rsquo;d be the right fit? Apply anyway! We&rsquo;d love to see your application.
 
 
 
 At ReadMe, we&rsquo;re committed to cultivating a diverse and inclusive workplace. We welcome people of all different backgrounds, experiences, abilities, and perspectives. We are an equal opportunity employer and a pleasant and supportive place to work. We'd love to have you come join us here! ReadMe is open to hiring folks fully remote in the US, hybrid, or in-person at our New York or San Francisco HQ.
 
 
 
</div>

DS Technologies Inc

<div><div><div>About US: We are a company that provides innovative, transformative IT services and solutions. We are passionate about helping our clients achieve their goals and exceed their expectations. We strive to provide the best possible experience for our clients and employees. We are committed to continuous improvement and innovation, and we are always looking for ways to improve our services and solutions. We believe in working collaboratively with our clients and employees to achieve success.</div>
<div></div>
<div>DS Technologies Inc is looking for Engineer II &ndash; Big Data / ETL Engineer (Apptio) role for one of our premier clients. 
</div><div>Job Title: Engineer II &ndash; Big Data / ETL Engineer (Apptio) 
Location: New York, NY (NYC Metro Area only)(Hybrid) 
Position Type: Contract 
Only W2 
 
Job Summary: 
We are looking for a highly skilled Big Data / ETL Engineer who can work as a standalone developer and write production-ready code from scratch. The ideal candidate has strong expertise in Python, SQL, ETL development, and data warehousing, with hands-on experience building scalable data pipelines in enterprise environments. 
 
Key Responsibilities:
</div><ul><li>Design, develop, and maintain ETL pipelines using Python from scratch</li>
<li>Write efficient, reusable, and scalable code following OOP principles</li>
<li>Develop and optimize complex SQL queries, stored procedures, and database objects</li>
<li>Perform data modeling including schemas and entity relationships</li>
<li>Build and manage Airflow DAGs</li>
<li>Ingest, cleanse, govern, and report data from Big Data platforms</li>
<li>Work with multiple SQL dialects (SQL Server, Oracle, DB2, PostgreSQL)</li>
<li>Collaborate with stakeholders while operating independently</li>
</ul><div>Required Skills &amp; Qualifications:</div>
<ul><li>Strong Python (ETL pipeline development from scratch)</li>
<li>Expert SQL and RDBMS concepts</li>
<li>MS SQL Server (SSIS, SSRS)</li>
<li>Oracle PL/SQL</li>
<li>Solid understanding of OOP principles</li>
<li>Apptio experience</li>
<li>Airflow (DAG development)</li>
<li>Experience with Data Warehousing &amp; Big Data</li>
<li>Node.js, JSON, and NoSQL databases</li>
<li>Ability to work as an independent contributor</li>
<li>Must be local to NYC metro area</li>
</ul><div>Nice to Have:</div>
<ul><li>PySpark / Apache Spark</li>
<li>Databricks Delta Lakehouse or BigQuery</li>
<li>Exposure to cloud-based business tools and platforms</li>
</ul>
</div>Flexible work from home options available.</div>

Engineer II – Big Data / ETL Engineer (Apptio)

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Engineer II – Big Data / ETL Engineer (Apptio)