Quality Analyst

Strong in Video Editor (Digital Content / Social Media / Lifestyle Brands)

Mandatory (Experience 1):Must have 2+ years of hands-on experience in video editing, working on digital content for social media or digital platforms (reels, posts, ads, event clips, product/lifestyle content).

Mandatory (Experience 2):Must have strong practical skills in Premiere Pro and/or After Effects, capable of turning raw footage into clean, engaging, and brand-consistent videos.

Mandatory (Experience 3):Experience in editing both short-form and long-form content, with attention to flow, timing, clarity, and storytelling across various digital formats

Mandatory (Skill 1):Strong understanding of pacing, sequencing, and narrative construction in videos, with ability to rework and refine edits based on feedback.

Mandatory (Skill 2):Ability to work independently, manage timelines, and consistently deliver high-quality videos in a fast-paced daily content environment.

Mandatory (Portfolio):Must showcase 2-3 video projects or content pieces demonstrating strong storytelling, technical editing skills, and adaptability to different formats/platforms.

Job Title : MLOps Engineer

Mode: Hybrid

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary:

We are looking for a skilled and proactive ML Engineer with strong expertise in Python, Databricks, and Machine Learning model development. The ideal candidate should be proficient in building scalable data pipelines and deploying ML models, with a working knowledge of MLOps principles and tooling. This role offers an opportunity to work on impactful AI/ML initiatives in a collaborative environment.

Key Responsibilities:

• Develop and maintain machine learning pipelines for training, testing, and deploying models

• Design and implement infrastructure for managing and monitoring machine learning models

• Work with data scientists to build scalable, efficient, and automated model training and testing processes

• Collaborate with software engineers to integrate machine learning models into production systems

• Automate and optimize the deployment and scaling of machine learning models in a distributed computing environment

• Monitor and troubleshoot machine learning systems and infrastructure to ensure high availability and performance

• Develop and maintain documentation and best practices for MLOps processes and procedures.

Experience:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

• 3+ years of experience in MLOps or related field, including building and deploying machine learning models at scale

•Proficiency in programming languages such as Python, Java, and C++

•Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras

• Experience with containerization technologies such as Docker and Kubernetes

• Strong understanding of DevOps principles and practices

• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud

AI-Native Software Developer Intern

Build real AI agents used daily across the company

We’re looking for a high-agency, AI-native software developer intern to help us build internal AI agents that improve productivity across our entire company (80–100 people using them daily).

You will ship real systems, used by real teams, with real impact.

If you’ve never built anything outside coursework, this role is probably not a fit.

What You’ll Work On

You will work directly on designing, building, deploying, and iterating AI agents that power internal workflows.

Examples of problems you may tackle:

Internal AI agents for:

• Knowledge retrieval across Notion / docs / Slack
• Automated report generation
• Customer support assistance
• Process automation (ops, hiring, onboarding, etc.)
• Decision-support copilots
• Prompt engineering + structured outputs + tool-using agents

Building workflows using:

• LLM APIs
• Vector databases
• Agent frameworks
• Internal dashboards
• Improving reliability, latency, cost, and usability of AI systems
• Designing real UX around AI tools (not just scripts)

You will own features end-to-end:

• Problem understanding
• Solution design
• Implementation
• Testing
• Deployment
• Iteration based on user feedback

What We Expect From You

You must:

• Be AI-native: you actively use tools like:
• ChatGPT / Claude / Cursor / Copilot
• AI for debugging, scaffolding, refactoring
• Prompt iteration
• Rapid prototyping
• Be comfortable with at least one programming language (Python, TypeScript, JS, etc.)
• Have strong critical thinking
• You question requirements
• You think about edge cases
• You optimize systems, not just make them “work”
• Be high agency
• You don’t wait for step-by-step instructions
• You proactively propose solutions
• You take ownership of outcomes
• Be able to learn fast on the job

Help will be provided but you will not be spoonfed.

Absolute Requirement (Non-Negotiable)

If you have not built any side projects with a visible output, you will most likely be rejected.

We expect at least one of:

• A deployed web app
• A GitHub repo with meaningful commits
• A working AI tool
• A live demo link
• A product you built and shipped
• An agent, automation, bot, or workflow you created

Bonus Points (Strong Signals)

These are not required but will strongly differentiate you:

• Built projects using:
• LLM APIs (OpenAI, Anthropic, etc.)
• LangChain / LlamaIndex / custom agent frameworks
• Vector DBs like Pinecone, Weaviate, FAISS
• RAG systems
• Experience deploying:
• Vercel, Fly.io, Render, AWS, etc.
• Built internal tools for a team before
• Strong product intuition (you care about UX, not just code)
• Experience automating your own workflows using scripts or AI

What You’ll Gain

You will get:

• Real experience building AI agents used daily
• Ownership over production systems
• Deep exposure to:
• AI architecture
• Product thinking
• Iterative engineering
• Tradeoffs (cost vs latency vs accuracy)
• A portfolio that actually means something in 2026
• A strong shot at long-term roles based on performance

If you perform well, you won’t leave with a certificate, you'll leave with real-world building experience.

Who This Is Perfect For

• People who already build things for fun
• People who automate their own life with scripts/tools
• People who learn by shipping
• People who prefer responsibility over structure
• People who are excited by ambiguity

Who This Is Not For

Be honest with yourself:

• If you need step-by-step instructions
• If you avoid open-ended problems
• If you’ve never built anything outside assignments
• If you dislike using AI tools while coding

This will be frustrating for you.

How To Apply

Send:

• Your GitHub
• Links to projects (deployed preferred)
• A short note explaining:
• What you built
• Why you built it
• What you’d improve if you had more time

Strong portfolios beat strong resumes.

About the Role:

As an Intune Engineer, you will primarily focus on migrating endpoints from SCCM to Microsoft Intune, managing co-management environments, and overseeing Intune infrastructure to ensure scalable, secure, and high-performance device management. You'll work closely with Microsoft 365 ecosystem tools and support enterprise-wide device provisioning, compliance, and security.

What You'll Do:

• Design, implement, and maintain Microsoft Intune infrastructure with ongoing integration to Microsoft 365 services
• Develop and enforce policies around secure device access, compliance, and application management
• Handle device enrollment, provisioning, and lifecycle management across Windows, iOS, and Android
• Develop automation scripts and collaborate with teams to streamline workflows
• Provide advanced Tier 3 support and training for complex Intune-related issues
• Manage Windows Autopilot and Azure AD integration for hybrid identity and seamless onboarding
• Lead security compliance checks and audit readiness through Intune policies

What We’re Looking For:

• 3-4 years of endpoint management experience with 2+ years in Microsoft Intune (SCCM migration experience is a big plus)
• Strong technical skills in Windows OS, Azure AD, Autopilot, conditional access, and device security
• Expertise troubleshooting device enrollment, app deployment, and security settings
• Familiarity with scripting (PowerShell, Graph API) and enterprise automation
• Microsoft 365 Certified Endpoint Administrator Associate or equivalent preferred
• Excellent communication skills with a team-first mindset

Job Description

Den monk is hiring for a Tele-sales Executive at its own office in Janakpuri, New Delhi. The job roles and responsibilities are given below:

·        Initiate Outbound Calls to Potential B2B Customers Using Established Sales Scripts and Strategies to Generate Leads and Close Sales Deals.

·        Identify Business Needs and Provide Accurate Information About Products Including Features, Benefits, And Pricing, While Understanding the Customer's Industry, Market, And Pain Points.

·        Develop and Nurture Relationships with Potential Customers, Understand Their Business Requirements, And Provide Tailored Solutions to Meet Their Needs.

·        Conduct Research to Identify and Target Potential B2B Customers, Including Market Segments, Industries, And Geographic Regions.

·        Follow Up on Leads and Inquiries Received Via Phone, Email, Or Other Communication Channels in A Timely and Professional Manner.

·        Stay Updated on Product Knowledge, Industry Trends, And Competitor Activities to Effectively Position Products or Services in The B2B Market. Prepare and Present Sales Proposals, Negotiate Pricing and Contract Terms, And Close Sales Deals.

·        Qualifications and Requirements: Bachelor's Degree in Business, Marketing, Or A Related Field, With Relevant Experience in Inside Sales and business development.

·        Preferably in A B2B Environment. 

Key Skills:

            Programming Languages: C#, VB.NET

            Server-Side Technologies: ASP.NET

            Front-End Technologies: Html5, ES5/ES6/ JavaScript, CSS, jQuery, Bootstrap, Ajax, Web

             Sockets

            Database: SQL Server

            Knowledge on below concepts/technologies is an added advantage

            - Cloud Platforms: Azure / Google

            - NodeJS, Mongo DB

            - Redis, RabitMQ, MQTT, Kafka

            - Concept of Continuous Integration / Continuous Deployment

Key Deliverables: Writing codes as per the requirement.

Desired Candidate Profile

• Graduation/ Post graduation in any discipline from a reputed institution
• 3+ years’ experience in the digital advertising domain, with CPS experience
• Record of working with cross functional teams and external partners
• Ability to multitask in a high pressure environment
• Basic finance understanding to manage the overall revenue and cost reconciliation
• A mindset of troubleshooting/ problem solving as required
• Maniacal attention to detail and very strict adherence to timelines

• Managing the solving of problems concerning the test automation infrastructure
• Understand and maintain Test Automation Frameworks.
• Follow the coding standards and code walk through.
• Maintain Automation Standards and Processes documentation.
• Write automated test scripts under the direction of the Test Automation Lead.
• Ability to work independently on tasks / modules assigned related to automation
• Monitoring of and reporting on the progress of the test automation process
• Reporting on the quality of the test object
• Raise risks on time and provide alternate solutions to mitigate the risk
• Advice and support for the implementation of all types of tools

About Turing:

Turing enables U.S. companies to hire the world’s best remote software engineers. 100+ companies including those backed by Sequoia, Andreessen, Google Ventures, Benchmark, Founders Fund, Kleiner, Lightspeed, and Bessemer have hired Turing engineers. For more than 180,000 engineers across 140 countries, we are the preferred platform for finding remote U.S. software engineering roles. We offer a wide range of full-time remote opportunities for full-stack, backend, frontend, DevOps, mobile, and AI/ML engineers.

We are growing fast (our revenue 15x’d in the past 12 months and is accelerating), and we have raised $14M in seed funding (https://tcrn.ch/3lNKbM9">one of the largest in Silicon Valley) from:

• Facebook’s 1st CTO and Quora’s Co-Founder (Adam D’Angelo)
• Executives from Google, Facebook, Square, Amazon, and Twitter
• Foundation Capital (investors in Uber, Netflix, Chegg, Lending Club, etc.)
• Cyan Banister
• Founder of Upwork (Beerud Sheth)

We also raised a much larger round of funding in October 2020 that we will be publicly announcing over the coming month. 

Some articles about Turing:

• https://techcrunch.com/2020/08/25/turing-raises-14m-to-help-source-vet-place-and-manage-remote-developers-in-tech-jobs/">TechCrunch: Turing raises $14M seed to help source, vet, place, and manage remote developers
• https://www.theinformation.com/articles/six-startups-prospering-during-coronavirus">The Information: Six Startups Prospering During Coronavirus
• https://medium.com/@cyanbanister/turing-helps-the-world-level-up-ff44b4e6415d">Cyan Banister: Turing Helps the World Level Up
• https://turing.com/boundarylessblog/2019/10/the-future-of-work-is-remote/the-future-of-work/">Jonathan Siddharth (Turing CEO): The Future of Work is Remote.

Turing is led by successful repeat founders Jonathan Siddharth and Vijay Krishnan, whose last A.I. company leveraged elite remote talent and had a successful acquisition. (https://techcrunch.com/2017/02/23/revcontent-acquires-rover/">Techcrunch story). Turing’s leadership team is composed of ex-Engineering and Sales leadership from Facebook, Google, Uber, and Capgemini.

About the role:

Software developers from all over the world have taken 200,000+ tests and interviews on Turing. Turing has also recommended thousands of developers to its customers and got customer feedback in terms of customer interview pass/fail data and data from the success of the collaboration with a U.S customer. This generates a massive proprietary dataset with a rich feature set comprising resume and test/interview features and labels in the form of actual customer feedback. Continuing rapid growth in our business creates an ever-increasing data advantage for us. 

We are looking for a Machine Learning Scientist who can help solve a whole range of exciting and valuable machine learning problems at Turing. Turing collects a lot of valuable heterogeneous signals about software developers including their resume, GitHub profile and associated code and a lot of fine-grained signals from Turing’s own screening tests and interviews (that span various areas including Computer Science fundamentals, project ownership and collaboration, communication skills, proactivity and tech stack skills), their history of successful collaboration with different companies on Turing, etc. 

A machine learning scientist at Turing will help create deep developer profiles that are a good representation of a developer’s strengths and weaknesses as it relates to their probability of getting successfully matched to one of Turing’s partner companies and having a fruitful long-term collaboration. The ML scientist will build models that are able to rank developers for different jobs based on their probability of success at the job. 

     
 You will also help make Turing’s tests more efficient by assessing their ability to predict the probability of a successful match of a developer with at least one company. The prior probability of a registered developer getting matched with a customer is about 1%. We want our tests to adaptively reduce perplexity as steeply as possible and move this probability estimate rapidly toward either 0% or 100%; maximize expected information-gain per unit time in other words. 

As an ML Scientist on the team, you will have a unique opportunity to make an impact by advancing ML models and systems, as well as uncovering new opportunities to apply machine learning concepts to Turing product(s).

This role will directly report to Turing’s founder and CTO, https://www.linkedin.com/in/vijay0/">Vijay Krishnan. This is his https://scholar.google.com/citations?user=uCRc7DgAAAAJ&;hl=en">Google Scholar profile. 

Responsibilities:

• Enhance our existing machine learning systems using your core coding skills and ML knowledge.
• Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems.
• Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics.
• Design features and builds large scale recommendation systems to improve targeting and engagement.
• Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers.

Minimum Requirements:

• BS, MS, or Ph.D. in Computer Science or a relevant technical field (AI/ML preferred).
• Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
• Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance and Data mining, understanding of NLP approaches like W2V or Bert.
• 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing.
• Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them.
• Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
• Good understanding of mathematical foundations of machine learning algorithms.
• Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST).

Other Nice-to-have Requirements:

• First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals. 
• Strong performance in Kaggle competitions.
• 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
• Strong communication skills.
• Experienced in leading large-scale multi-engineering projects.
• Flexible, and a positive team player with outstanding interpersonal skills.