Role 

We are looking for a Staff Threat Researcher to join our Threatlabz team. This is a hybrid role based in Mohali,reporting to the Senior Manager, Threat Research. As a key contributor to our threat research initiatives, you will lead the charge in identifying vulnerabilities and analyzing sophisticated malware within the Apple ecosystem. Your expertise in macOS and iOS system internals will drive the development of advanced detection strategies and strengthen our overall product defenses.

What you’ll do (Role Expectations)

• Perform static and dynamic analysis of macOS and iOS applications, firmware, and system internals to identify vulnerabilities and malicious functionality
• Reverse-engineer malware samples to decipher behavior, capabilities, and attack vectors while contributing to prevention strategies
• Research and maintain deep expertise in macOS security features, XNU kernel updates, and frameworks such as Endpoint Security and Network Extensions
• Develop custom tools and scripts to automate reverse engineering, binary analysis, and malware-related processing tasks
• Partner with engineering, QA, and threat intelligence teams to integrate new security features and harden product defenses

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• Proficiency in system-level languages including C, C++, Objective-C, Swift and deep knowledge of macOS architecture, Mach-O binary formats, and security mechanisms like SIP, TCC, and Gatekeeper
• Extensive hands-on experience with reverse engineering tools such as IDA Pro, Ghidra, Binary Ninja, Frida, and Wireshark
• Strong scripting skills, particularly in Python, for automating complex analysis and research tasks
• Proven ability to decompile, disassemble, and de-obfuscate closed-source binaries to reconstruct logic without source code access

What Will Make You Stand Out (Preferred Qualifications)

• Experience with Windows or Linux platforms for comparative threat analysis
• Prior professional track record in specialized malware analysis or vulnerability research
• Thorough understanding of network protocols and system-level communication mechanisms

#LI-Hybrid
#LI-RG

About Truveta 

Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US.   

Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.  

The Role 

We are seeking a highly motivated Postdoctoral Researcher to explore and develop novel applications of cutting-edge AI/ML technologies on large-scale real-world clinical data. 

This role is designed for recent PhD graduates who are passionate about pushing the boundaries of machine learning in healthcare. You will work at the intersection of machine learning, clinical data, and biomedical science, identifying new opportunities where modern AI can unlock insights that were previously out of reach. 

A key expectation is not just execution—but imagination: the ability to envision and prototype entirely new ways to use rich patient data to solve meaningful healthcare problems. 

What You’ll Do 

• Innovate: Identify and propose novel, high-impact applications of AI/ML using large-scale EHR data 

• Research & Prototype: Design, develop, and evaluate state-of-the-art models (e.g., foundation models, multimodal learning, causal ML, generative AI) 

• Work Across Modalities: Integrate structured and unstructured EHR data with emerging data types such as genomics, imaging, and clinical notes 

• Collaborate Cross-Functionally: Partner with clinicians, data scientists, and product teams to translate research ideas into real-world solutions 

• Publish & Share: Contribute to top-tier conferences/journals and represent Truveta in the research community 

• Explore the Unknown: Proactively identify problems that have not yet been addressed and define new research directions 

What We’re Looking For 

Minimum Qualifications 

• PhD in Computer Science, Machine Learning, Biomedical Informatics, or a related field 

• Strong background in machine learning, deep learning, or statistical modeling 

• Experience applying ML to healthcare, biomedical, or clinical datasets 

• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) 

Preferred Qualifications 

• Experience with healthcare data (EHRs, claims, clinical notes) or biomedical data (genomics, imaging) 

• Familiarity with cutting-edge areas such as:  

• Foundation models / LLMs in healthcare 

• Multimodal learning 

• Causal inference 

• Representation learning on longitudinal data 

• Track record of publications in top-tier ML or healthcare venues (e.g., NeurIPS, ICML, ICLR, MLHC, AMIA) 

• Ability to work across disciplines and communicate with both technical and clinical stakeholders 

Who You Are 

• Curious and imaginative: You naturally think beyond existing solutions and ask “what hasn’t been done yet?” 

• Impact-driven: You care about applying research to real-world healthcare problems 

• Comfortable with ambiguity: You thrive in open-ended environments where defining the problem is part of the job 

• Collaborative: You enjoy working across domains and learning from experts in different fields 

Why This Role is Unique 

• Access to one of the largest and richest longitudinal EHR datasets in the US 

• Opportunity to work on previously infeasible problems at the intersection of AI and medicine 

• A balance of academic-style research freedom and real-world impact 

• Collaboration with leading healthcare systems and industry partners 

Example Problem Areas (Illustrative) 

• Learning patient trajectories using foundation models for clinical decision support 

• Discovering novel phenotypes or disease subtypes from multimodal data 

• Predicting treatment effectiveness using causal ML on real-world data 

• Generating synthetic cohorts for rare disease research 

• Integrating genomics + EHR for precision medicine applications 

Software Engineer (AI Platforms)

About SingleStore

At SingleStore, we’re not just building a database company, we’re defining the future of data management. Going beyond multi-cloud, we offer customers flexible networking, storage, and compute options to meet their requirements. With a few clicks, our cloud service spins up production grade infrastructure using the latest capabilities of major cloud providers and the industry standard Kubernetes ecosystem.

As data systems evolve, the “database” is no longer just where queries run, it’s becoming the foundation for realtime AI applications: retrieval, reasoning, agent workflows, and intelligent automation over enterprise data. That’s the direction we’re building toward.

About the AI Platform Team

We build the software platform that powers AI native experiences across SingleStore: AI/ML capabilities, agent runtimes, tool integration, and the operational layer required to run these systems reliably at scale. Our work sits at the intersection of distributed systems, cloud infrastructure, and practical applied AI.

This team is not “pure research”, it’s engineering heavy. You’ll build product grade systems that let customers safely and reliably use AI on their data.

Role Summary

We are looking for a Software Engineer to design and implement core platform capabilities for AI/ML and AI Agents in SingleStore Cloud. You’ll work on services that enable model/tool orchestration (e.g.  MCP style tool discovery and execution), agent workflows, retrieval pipelines (embeddings/vector search), evaluation/observability, and secure multi tenant operations.

You will likely find yourself using Go and Python, Kubernetes, cloud primitives, and the right tools for the job,  while applying solid AI/ML fundamentals to make correct engineering decisions.

Role and Responsibilities

• Build and evolve backend services that power AI features: agent orchestration, tool execution, retrieval/RAG pipelines, and model serving integrations.
• Design APIs and control plane workflows for AI platform components (tenant-aware, secure by default, observable).
• Implement MCP style tool discovery / integration patterns so agents can safely call tools, connectors, and internal services.
• Work closely with product managers, designers, customers, and partner engineering teams to deliver high quality AI experiences.
• Engineer for reliability and scale: latency, cost controls, rate limiting, fallbacks, rollouts, and incident response readiness.
• Establish best practices around evaluation: offline test sets, regression detection, prompt/model/version tracking, and quality gates.
• Contribute to secure AI by design approaches: permissions, data access boundaries, prompt injection defenses, and auditability.
• Mentor junior engineers and contribute to a welcoming, high ownership team environment.

Required Skills and Experience

This is a software engineering role that requires strong fundamentals plus working knowledge of AI/ML concepts.

• Strong software engineering skills with experience in distributed systems (Go, Python, or similar).
• Experience building cloud native services: Kubernetes, containers, service-to-service APIs, CI/CD.
• 4+ years of experience working on a SaaS product or production platform.
• Solid understanding of AI/ML fundamentals (you don’t need to be a researcher, but you should understand concepts well enough to build correct systems):
• Supervised learning basics (training vs inference, overfitting, evaluation metrics, classification, anomaly detection, forecasting, regression etc.)
• LLM basics (tokens, context windows, prompting, tool/function calling concepts)
• Embeddings + vector search fundamentals (similarity, indexing tradeoffs, retrieval pitfalls)
• Strong debugging and problem-solving skills, including incident-style troubleshooting across services and infrastructure.
• Intellectual curiosity about investigating issues that impact product quality, reliability, latency, and business metrics.
• Passion for building robust, maintainable systems in a fast-paced, team-oriented environment.

Nice to Have (Preferred)

• Hands on experience with AI agents and orchestration frameworks (tool calling, workflows, planners/executors).
• Practical experience with RAG systems, reranking, grounding, and evaluation strategies.
• Experience with model serving patterns (batch/online inference, caching, streaming responses).
• Knowledge of security considerations for AI systems (data isolation, RBAC, prompt injection threats, audit logs).
• Familiarity with vector databases or vector capabilities in modern data platforms.
• Experience with observability stacks (structured logging, metrics, tracing) and SLO driven engineering.

Tech Stack

Go, Python, Kubernetes, cloud infrastructure, distributed systems, APIs, and modern AI tooling (LLM providers, embeddings, retrieval systems, eval/observability pipelines), ML tooling.