Internal Audit Jobs

POSITION: CONSULTANT PHYSICIAN/CONSULTANT MEDICINE QUALIFICATION:MD/DNB IN INTERNAL OR GENERAL MEDICINE EXPERIENCE: ANY EXPERIENCE 0 TO 25 YEARS AGE: MAX UPTO 56 YEARS SALARY BUDGET: 3.0 TO 4.0 LACS PM, DEPENDING UPON EXPERIENCE AND JOB KNOWLEDGE. LOCATION: BEHROR, RAJASTHAN, NEAR GURGAON, APPROX 110 KMS FROM DELHI AIRPORTON DELHI-JAIPUR EXPRESSWAY. HOSPITAL: A 50 BEDDED, WELL ESTABLISHED, MULTISPECIALTY HOSPITAL IN NEEMRANA, RAJASTHAN APPROX 90 KMS FROM DELHI AIRPORT ON DELHI - JAIPUR EXPRESSWAY. STATE OF ART INFRASTRUCTURE, LATEST MACHINERY & EQUIPMENT AND MOST MODERN TECHNOLOGY. THE HOSPITAL IS RUN BY A SEASONED MEDICAL PROFESSIONAL AND SUCCESSFULLY RUNNING FOR THE LAST 7+ YEARS. Interested candidates are requested to send us your cv on recruiterdoctors at the rate gmail.com. If spouse is a medico, please send us both CVs. If not interested, please help us with suitable references and share this job in your group. You can share your cv with us for future reference or for your preferred locations jobs also. Please note that we donot charge any type of fee from the candidates, it is absolutely free service. Regards, Team Doctors Recruiter Chandigarh

Carry out internal estimation processes for preparation of cost estimates for competitive bidding for budget or to provide baseline value for procurement proposals along with carry out Price Variation Calculation proposals for the business. Source: Adani Group | Job ID: 53018

We are Datadog's in-house product experts. The Technical Solutions team enables Datadog’s worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. As a Technical Account Manager 2 (TAM 2), you’ll serve as a trusted advisor to our strategic customers, accelerating their adoption of the Datadog platform and enabling long-term success. TAM 2s bring deep technical expertise, refined customer skills, and consultative insight into how monitoring, observability, and DevOps practices translate to business value. At Datadog, we place value in our office culture—the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Act as a technical advisor to 3 primary enterprise accounts, ensuring successful product adoption and effective usage of the Datadog platform. Lead enablement and adoption sessions across core product areas tailored to your customer’s architecture and business needs. Analyze customers’ IT Operations environments and workflows to recommend configuration, product usage, and performance improvements. Deliver technical business reviews, health checks, and account maturity assessments, contributing to customer QBRs with impactful recommendations. Escalate product issues appropriately and advocate for your customers’ needs with Datadog’s Product and Engineering teams. Create executive-level summaries and insights that tie platform usage to business outcomes. Participate in internal TAM strategy sessions and contribute to team learning through feature presentations, case studies, or best-practice sharing Who You Are: You have 2+ years of experience in a technical customer-facing role (TAM, Solutions Architect, SRE, DevOps Engineer, or similar) within the cloud or observability space. You’re confident with at least two public cloud platforms (e.g. AWS, Azure, GCP)

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the alignment of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: Develop and publish research on techniques for understanding representations of deep networks. Engineer infrastructure for studying model internals at scale. Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter . Show enthusiasm for long-term AI safety & alignment, and have thought deeply about technical paths to safe AGI. Bring experience in the field of AI safety & alignment, mechanistic interpretability, or spiritually related disciplines. Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. Possess 2+ years of research engineering experience and proficiency in Python or similar languag

Cloud Operations Engineers are responsible for building internal tools and process automation. Day-to-day duties are creating and monitoring systems alert dashboards, reviewing critical event and system logs, accessing customer instances that underpin their production databases, and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. We are looking for a Lead with strong technical leadership experience as well as technical depth who is looking to collaborate closely with Cloud Operations Engineering Management in building and maintaining a high-performing team that delivers high quality outcomes while fostering psychological safety and professional growth. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Core responsibilities Team leadership: partner with and assist COE Management with the tasks of providing ongoing technical feedback to engineers, support their growth and creating an inclusive team environment Execution and delivery: play a key role in guiding team members through project deliverables ensuring high quality outcomes while also assisting in meeting or resetting timelines when required Time management: between assisting team members with day to day tasks ranging from incident to project management Cross-functional collaboration: work closely with Product, Technical Services and R&D to surface team’s pain points and drive alignment with the goal of providing an excellent user experience to the end customer Coordinate with Lead counterparts within Cloud Operations as well as Technical Services to ensure our uptime guarantees to the MongoDB Atlas customer base Assist and collaborate with the team on scoping, designing, deploying and ongoing maintenance of systems that focus on reducing mean time to resolve customer incidents Detec

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Secrets Infrastructure team provides the cryptographic identity and secrets management foundation for Stripe. We build and operate the internal certificate authority that authenticates every person and service at Stripe, and the secrets platform that manages everything from financial partner credentials to infrastructure access keys. We build foundational security infrastructure at scale: our certificate authority issues mTLS client certificate identities for thousands of services and engineers, and our secrets platform and libraries protect access to critical financial systems and external partners across all of Stripe’s codebases, services, and platforms. The technical challenges include building systems with 99.99%+ availability, implementing TLS workload identity and attestation logic for new platforms, and designing secret management tools that are both secure and user-friendly. Our infrastructure must be both reliable and developer-friendly—we maintain libraries in Go, Java, Ruby, and Python. As a small team responsible for critical systems, engineers take on meaningful ownership. Through collaboration with teams across Stripe, you'll build and set direction for the authentication and secrets management underpin identity in distributed systems at scale. Secrets Infrastructure is a fully remote team, with a small presence in the Seattle and New York City offices. We pride ourselves on a friendly, technically rigorous, and supp

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: Develop and publish research on techniques for understanding representations of deep networks. Engineer infrastructure for studying model internals at scale. Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter . Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI. Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines. Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. Possess 2+ years of research engineering experience and proficiency in Python or similar languages. Are deeply curious. About OpenA

Procurement Analyst (Process&Supply Base Mgmt) Company: The Boeing Company Boeing Defense, Space & Security (BDS) has an exciting opportunity for an Experienced Procurement Analyst (Level 3) to join our dynamic team in Mesa, Arizona . Position Responsibilities: Analyze spend, supplier performance, market trends, and purchasing activity to identify savings opportunities and procurement risks Monitor and track supplier pricing updates against program targets/budgets Support contracting teams in sourcing events such as bidder boards and source selection boards. Support PBOM process from campaign kickoff through supply chain leadership review and approval Develop and maintain reports, dashboards, and metrics to monitor procurement performance Line of balance analysis to ensure purchase requisitions are released on purchase order with delivery dates in accordance with aircraft demand schedule Partner with engineering, operations, finance, supply chain, and program teams to understand requirements and support business objectives Recommend and implement process improvements to increase efficiency, accuracy, and cycle-time performance Build and maintain effective relationships with internal stakeholders This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location options. Shift: This position is for 1st shift. Basic Qualifications (Required Skills/Experience): More than 3 years of experience with Supplier Management or Procurement practices and processes More than 3 years of experience with Excel, Access, or

Should have good knowledge for this position. Address: Wipro EC4 Internal Road Shikaripalya Phase 1 Electronic City Bangalore Facility: BROADCOM BANGALORE - E C FS Qualification: Not Specified Experience: 1 - 2 years Source: Sodexo India | Job Code: IJP575715

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

Coordination Systems provides foundational distributed systems building blocks for internal Datadog platforms. Our services cover sharding, consensus, resource protection, configuration distribution, and much more. We are looking for a manager to lead the Coordination Systems - Storage team. This team provides essential configuration storage and distribution systems that are depended upon by almost every service and pod at Datadog. We power critical runtime configuration (e.g. feature flags), complex control planes (e.g. dynamic sharding configuration), and much more. Storage is one of four subteams within Coordination Systems. If successful, the candidate will have opportunities to lead other growing and impactful areas such as Resource Protection. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: (Describe role responsibilities here/max 6 bullets) Lead a core team of 5 engineers (distributed, with majority in NYC) Lead ceremonies, prioritize and delegate project Stay hands-on with the code, e.g. isolated features, small remediations, investigation follow ups Stay actively involved in operations, incidents, root cause analysis, etc. Constantly promote a culture of operational excellence, organizing gamedays, conducting operational reviews, staying proactive with reliability Who You Are: (Describe role qualifications here/max 6 bullets) Strong distributed systems skills, able to understand and account for a variety of failure modes, well-versed in end-to-end o11y, validation testing, simulation setup, etc. Worked on platform teams before, providing critical infrastructure to internal stakeholders Experienced in handling significant incidents, both as a responder and follow-up ow

ROLE SUMMARY: The key strategic focus within the Internal Medicine Research Unit (IMRU) is identifying novel therapies to prevent or treat metabolic diseases such as obesity and cardiovascular disease. Our goal is to build a world-class research team of dedicated scientists committed to developing a deep mechanistic understanding of the metabolic pathways underlying disease pathogenesis. As a senior scientific leader and member of the obesity discovery biology team, this individual will play a significant role in shaping the scientific direction for the obesity therapeutic area and influencing broader IMRU research strategy and portfolio priorities. The individual will help create and drive discovery research strategy across multiple programs, including target ideation, validation, translational biomarker strategy, hypothesis testing, and early clinical development within the IMRU obesity portfolio. The successful candidate will lead through both direct team leadership and influence across multidisciplinary partners, helping align scientific decisions across discovery biology, translational sciences, clinical, computational, and external collaborators. The individual will identify emerging therapeutic opportunities, advance portfolio programs with scientific rigor and urgency, and represent research strategies to internal leadership and the external scientific community. Knowledge and experience in the study of metabolic pathways are essential, and familiarity with the pathophysiology of dysmetabolic states would be advantageous. Strong self-motivation, excellent communication and interpersonal skills, and the ability to lead, mentor, and build scientific capability in a highly collaborative environment are essential. ROLE RESPONSIBILITIES: Shape and influence the scientific direction for discovery research programs aligned with IMRU therapeutic area and portfolio strategy. Ap

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for a Principal Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently . This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented , so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. What you’ll do Design and improve the platform systems that support model training, evaluation, an

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for an Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently . This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented , so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. What you’ll do Design and improve the platform systems that support model training, evaluation, and product