Inovalon is a leading cloud-based healthcare technology company that leverages data analytics and AI to drive meaningful improvements across the healthcare ecosystem. The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon’s central AI and machine learning hub. This team partners with Provider, Payer, and Pharmacy business units to identify, build, and deploy AI solutions that improve clinical and operational outcomes at scale. 

In this role, you will contribute to both classical machine learning and generative AI applications, including LLM-based and agentic solutions. You will work across the full model development lifecycle on a modern, cloud-native AWS stack, collaborating closely with AI Product Managers and a distributed team of senior engineers across the U.S. and India. 

Key Responsibilities

• Design, train, and deploy machine learning models spanning classical ML (classification, regression, clustering, time-series) and generative AI use cases including LLM-based and agentic applications. 
• Build and maintain cloud-native solutions on AWS using containerized architectures (Docker, Kubernetes) to support scalable model serving and data pipelines. 
• Own and contribute to the full Model Development Lifecycle (MDLC), including dataset versioning, model versioning, model registry management, and model evaluation frameworks. 
• Develop and integrate Python-based ML components that work seamlessly with existing product platforms across multiple business units. 
• Collaborate with AI Product Managers across the Insights BU and partner business units (Provider, Payer, Pharmacy) to translate business needs into AI solutions. 
• Apply neural networks and deep learning techniques using PyTorch for appropriate use cases alongside scikit-learn-based classical approaches. 
• Write robust, production-ready code following engineering best practices; participate in code and design reviews. 
• Leverage AI coding tools (such as Claude Code or equivalent) as part of your daily development workflow to improve velocity and code quality. 
• Mentor junior engineers and contribute to team knowledge-sharing around ML best practices, tooling, and architecture decisions. 
• Support integration of frontend components into ML-powered features where applicable. 
• Contribute to retrospectives and team process improvements; actively participate in sprint planning and end-of-iteration demos. 
• Adhere to all HIPAA, data governance, confidentiality, and regulatory requirements in all aspects of work. 
• Maintain compliance with Inovalon’s policies, procedures, and mission statement, fulfilling responsibilities that support operational and financial success. 

Qualifications

Required 

• Minimum 5 years of software development experience with a strong foundation in machine learning fundamentals and model training. 
• Expert-level Python proficiency; Python is the team’s primary language and is the highest-priority technical requirement. 
• Hands-on experience building and deploying classical ML models in production using scikit-learn. 
• Demonstrated experience with generative AI, LLMs, or agentic application development. 
• Proficiency with PyTorch and neural network architectures. 
• Practical knowledge of the Model Development Lifecycle (MDLC): dataset versioning, model versioning, model registry, and model evaluation. 
• AWS cloud experience, including deploying and managing cloud-native workloads. 
• Containerization experience with Docker and/or Kubernetes. 
• Strong problem-solving ability; demonstrated capacity to work independently and take ownership of complex technical challenges. 
• Daily usage of AI-assisted coding tools (e.g., Claude Code, GitHub Copilot, or similar) as part of standard development workflow. 

Preferred 

• Experience with database technologies (SQL or NoSQL); familiarity with data pipeline tooling. 
• Frontend development skills to support full-stack ML feature work. 
• Healthcare domain experience or exposure to HIPAA-regulated environments. 

Education 

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related technical field required. 
• Master’s degree or PhD in Computer Science, Machine Learning, or equivalent practical experience preferred. 

Physical Demands and Work Environment 

• Sedentary work (i.e., sitting for long periods of time). 
• Exerting up to 10 pounds of force occasionally and/or a negligible amount of force. 
• Subject to inside environmental conditions. 
• Travel for this position will include less than 10% locally, usually for training purposes. 

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Overview

Zeta Global is seeking a Lead Software Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows.

This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability.

The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments.

What You’ll Build

• Full-stack applications supporting HCP and patient (DTC) audience discovery, segmentation, and activation
  • Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
  • Identity resolution and data linkage services across fragmented data sources
  • Reporting, attribution, and measurement systems connecting campaigns to outcomes
  • APIs and services enabling downstream activation, analytics, and partner integrations

Key Responsibilities

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
  • Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
  • Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
  • Implement identity resolution logic including matching, deduplication, and graph-based linkage
  • Ensure high data quality through validation, reconciliation, and monitoring frameworks
  • Design systems with strong security controls, including encryption, access control, and auditability
  • Apply privacy-by-design principles across all systems handling PHI/PII
  • Partner with Product and Data teams to translate healthcare requirements into scalable architectures
  • Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
  • Mentor engineers and act as a technical leader across the team

Engineering Expectations

• Strong experience designing distributed systems (microservices, event-driven architectures)
  • Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
  • Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
  • Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
  • Experience building modern front-end applications (React or similar)
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
  • Experience implementing observability (logging, metrics, tracing) and reliability patterns
  • Strong understanding of performance optimization and scalability tradeoffs

Healthcare & Domain Expectations

• Experience working with HCP data (provider identity, targeting, segmentation)
  • Experience with patient / DTC data workflows and privacy-aware systems
  • Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
  • Familiarity with identity graphs and data onboarding patterns
  • Experience building reporting or attribution systems tied to business outcomes
  • Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements

Qualifications

• 8–10 years of software engineering experience with increasing technical ownership
  • Proven track record of building and scaling data-intensive or distributed systems
  • Experience working in regulated environments (healthcare strongly preferred)
  • Strong system design and architecture skills
  • Ability to lead technically while remaining hands-on in implementation
  • Strong collaboration skills across engineering, product, and data teams

Preferred

• Experience with healthcare data providers or identity ecosystems
  • Background in AdTech, MarTech, or audience/data platforms
  • Experience with privacy-enhancing technologies (tokenization, clean rooms)
  • Exposure to ML/AI-driven data products or analytics systems

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $215,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-TS1

We’re seeking a Staff DevOps Engineer to join our Cloud Platform Team — the engineer who sets the technical direction for how Built’s infrastructure is designed, operated, and evolved. This is the most senior individual contributor role on the platform team, and it goes well beyond day-to-day operations. You’ll architect the systems that every engineering team at Built depends on, define the standards that others work within, and drive the platform roadmap with full autonomy. By raising the reliability and velocity of our infrastructure, you directly enable Built’s mission of radically disrupting construction finance.

Our Guiding Principles

• Be Bold. We pursue the biggest problems in our industry, challenge assumptions others take for granted, and take calculated risks to get there. We don’t hide behind consensus or committees. Playing it safe is just failing slowly.
• Help Customers Win. We learn our customers’ businesses deeply — how they think, how they deploy capital, what keeps them up at night. We treat their capital like our own. We ship leverage, not features. And we measure ourselves by customer results, not our intentions.
• Move with Urgency & Purpose. We bias toward delivery over perfection, remove friction from our own paths, and communicate in real time. Momentum compounds — and we build it every day.
• Own the Outcome. We own outcomes, not just tasks. We hold a high Say:Do ratio and take responsibility from idea through impact. When something breaks, we fix it — we don’t wait to be asked.
• Never Satisfied. We raise the bar continuously. We stay curious, hold exacting standards, debate hard, and hold our opinions loosely when the evidence shifts. Excellence is a habit, not an event.

What You’ll Do

• Architect and own Built’s core cloud infrastructure on AWS — defining the patterns, standards, and systems that all engineering teams build on, from EKS/ECS cluster design to VPC topology to IAM governance.
• Lead platform modernization — driving the migration and simplification of our software delivery lifecycle, rationalizing tooling, and building the infrastructure foundation for Built’s AI-related product initiatives.
• Own SLOs and SLIs for the platform — define them, instrument them in your observability stack, and lead the team in meeting reliability targets consistently across all environments.
• Define DevOps engineering standards across the team — IaC patterns, CI/CD architecture, container orchestration standards, and observability frameworks.
• Drive the platform roadmap in partnership with engineering leadership — balancing foundational investment with immediate delivery needs and communicating trade-offs clearly to technical and non-technical stakeholders.
• Lead incident response and postmortems — serve as the technical escalation point for complex infrastructure failures, drive systemic improvements, and reduce incident volume over time.
• Evaluate and adopt new technologies across the platform stack — making sound build-versus-buy decisions with a clear view of long-term trade-offs and ROI.
• Mentor a team of 5 platform engineers through design reviews, pairing, architecture guidance, and knowledge-sharing sessions across the broader engineering organization.
• Partner with Information Security to lead vulnerability assessment and security architecture — ensuring compliance, proactive risk management, and adherence to regulatory requirements.

Skills & Experience

Must-Have

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of hands-on experience in DevOps, platform engineering, or cloud infrastructure in a production environment.
• Expert-level AWS knowledge — deep fluency with EKS, ECS, EC2, RDS, S3, IAM, VPC, and cost management tooling.
• Deep Kubernetes expertise — cluster architecture, networking, RBAC, autoscaling, and debugging production workloads at scale.
• Strong infrastructure-as-code proficiency with Terraform — writing extensible, maintainable modules and enforcing IaC standards across the team.
• Proven experience designing and operating CI/CD pipelines with GitHub Actions, CircleCI, or similar tooling.
• Hands-on observability experience with Datadog, Grafana, or similar platforms — metrics, logs, traces, monitors, SLO tracking, and alerting.
• Familiarity with incident management tooling (Incident.io, PagerDuty, or similar) and a track record of leading postmortems and driving systemic reliability improvements.
• Fluency in at least one scripting or automation language — Python, Go, or Bash.
• Strong communication skills — able to present infrastructure risks and architectural trade-offs to both engineers and non-technical stakeholders.

Nice-to-Have

• Experience with other IaC tools (Pulumi, CloudFormation, CDK) is a plus.
• Experience with service catalog and developer experience tooling (OpsLevel, Backstage, or similar).
• Background in fintech, lending, or regulated industries where uptime, auditability, and data security are critical.
• FinOps experience — cloud cost governance, right-sizing, and spend transparency across engineering teams.
• Contribution to open-source infrastructure projects or published engineering RFCs.

What the First Year Looks Like

Days 1–30: Learn the Landscape

• Ramp up on Built’s AWS infrastructure (EKS, ECS, VPC, IAM), CI/CD pipelines, and observability stack.
• Shadow on-call rotations (roughly one week every six weeks) to understand current incident patterns and pain points firsthand.
• Build relationships with product engineering teams to understand their infrastructure dependencies and friction points.

Days 30–60: Start Shaping the Platform

• Identify the highest-leverage opportunities for platform modernization and SDLC simplification.
• Begin contributing to architecture decisions and TRDs for current initiatives.
• Propose improvements to IaC standards, deployment pipelines, or observability coverage where gaps exist.

Days 60–90: Own and Drive

• Lead a meaningful platform initiative from architecture through delivery — whether modernization, reliability, or developer experience.
• Establish yourself as the technical standard-setter the team turns to for complex infrastructure and AI-related platform questions.
• Contribute to the roadmap planning process with a clear point of view on what the platform needs next.

AI & Technology Expectations

At Built, AI is a first-class part of how we work — not a pilot program. For this role specifically, that means:

• Use AI coding assistants (your choice of platform) as a daily productivity multiplier for IaC authoring, pipeline configuration, and automation scripting.
• Apply AI to platform operations: runbook generation, incident summarization, root cause analysis drafts, and postmortem synthesis.
• Drive and contribute to Built’s broader initiative to automate the software delivery lifecycle — identifying where AI can reduce manual toil across build, test, deploy, and observe workflows.
• Evaluate emerging AI infrastructure tooling and bring well-reasoned recommendations to the team.
• Share effective AI use cases and patterns with the broader engineering organization.

Operational Details

• Team size: You’ll join a team of 5 platform engineers, with this role serving as the senior technical anchor.
• On-call: Rotations run approximately one week every six weeks. We work continuously to reduce incident volume and toil so that on-call is manageable and low-noise.
• Location: Remote (US). Flexible working hours.

Built’s salary range for this position is $175,000-$235,000 USD per year. The pay range is designed to accommodate upward mobility in the role, therefore it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees. Your total rewards package at Built will include equity, top-notch medical, dental and vision coverage, an unlimited PTO policy, and other benefits.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.