software engineer

engineer specials

engineering manager

ai / ml engineer

ai engineer

ai ml engineer

HDFC Bank

<div>
 
 
 Job Purpose
 
 
 
 An experienced AI/ML Engineer to design, develop and maintain AI / ML and GenAI based solutions on enterprise platform on Industry best and open-source models at scale along with governance and security frameworks
 
 
 
 Job Responsibilities (JR): 6 &ndash; 8 Areas
 
 
 
 
 Actionable (4-6)
 
 
 <ul>
 <li>
 Design and implement the necessary infrastructure (e.g., compute clusters, storage, networking) for AI applications, including cloud platforms like AWS, Azure, or GCP
 </li>
 <li>
 Design, build, and train generative AI models using techniques like deep learning and neural networks
 </li>
 <li>
 Develop and maintain scalable, efficient, and reliable data pipelines for AI models, ensuring data quality and integrity.
 </li>
 <li>
 Integrate machine learning models into AI platforms and deploy them into production environments, often using AIOps, MLOps and LLMOps frameworks
 </li>
 <li>
 Design and implement monitoring strategies for AI platforms and optimize their performance for scalability and real-time applications.
 </li>
 <li>
 Perform machine learning tests and statistical analysis to fine-tune the machine learning systems
 </li>
 <li>
 Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, performance evaluation and training of AI/ML solutions Extend existing machine learning libraries and frameworks
 </li>
 <li>
 Implemented and evaluated machine learning models, including supervised, unsupervised, and reinforcement learning techniques, for B2C use cases
 </li>
 <li>
 Strong experience with deep learning frameworks like TensorFlow and PyTorch
 </li>
 <li>
 Used Python or other programming models to build and train a deep learning model for Document Classification, Extraction, Signature matching, STT, TTS kind of use cases
 </li>
 <li>
 Demonstrated ability to fine-tune and optimize models using large data sets
 </li>
 <li>
 Certified in AI/ML in any of the cloud platforms like AWS, Azure, or GCP and experience deploying AI/ML models in the cloud
 </li>
 <li>
 Effective communication skills, both written and verbal, with the ability to effectively communicate technical concepts to non-technical audiences
 </li>
 </ul>
 
 
 Key Skills :
 
 
 <ul>
 <li>
 Strong background in designing and implementing machine learning and deep learning algorithms and responsible AI practices at enterprise scale and speed
 </li>
 <li>
 Working knowledge with ML platforms like TensorFlow, PyTorch, or Hugging Face
 </li>
 <li>
 Proficiency in Training, Tuning and Deploying GenAI models based on LLMs, GANs, and VAEs
 </li>
 <li>
 Hands on expert in programming languages like Python, Java, or C++, and have experience with cloud platforms, containerization technologies (e.g., Docker, Kubernetes), and data pipeline tools (e.g., Apache Kafka, Spark)
 </li>
 <li>
 Experience working in cross-functional teams
 </li>
 <li>
 Strong analytical and problem-solving skills
 </li>
 </ul>
 
 
</div>

AI / ML Engineer

Rakuten Symphony

<div>
 
 
 Job Title: AI/ML Engineer (Generative AI &amp; ML Ops)
 
 
 
 Minimum 5 to 8+ years of experience in AI/ML development.
 
 
 
 Location: Bangalore (Hybrid)
 
 
 
 
 
 
 
 Why should you choose us?
 
 
 
 Rakuten Symphony is a Rakuten Group company, that provides global B2B services for the mobile telco industry and enables next-generation, cloud-based, international mobile services. Building on the technology Rakuten used to launch Japan&rsquo;s newest mobile network, we are taking our mobile offering global. To support our ambitions to provide an innovative cloud-native telco platform for our customers, Rakuten Symphony is looking to recruit and develop top talent from around the globe. We are looking for individuals to join our team across all functional areas of our business &ndash; from sales to engineering, support functions to product development. Let&rsquo;s build the future of mobile telecommunications together!
 
 
 
 
 
 
 Required Skills and Expertise:
 
 
 
 
 AI/ML Strategy and Leadership
 
 :
 
 <ul>
 <li>
 Define the AI/ML strategy and roadmap aligned with the product vision.
 </li>
 <li>
 Identify and prioritize AI/ML use cases, including classical ML, Generative AI, and Agentic AI, relevant to our product offerings.
 </li>
 <li>
 Build and lead a high-performing AI/ML team by mentoring and upskilling existing non-AI/ML team members.
 </li>
 <li>
 Stay updated with the latest advancements in AI/ML, generative AI, Agentic AI and ML Ops, and apply them to solve business problems.
 </li>
 </ul>
 
 
 
 
 
 AI/ML Development
 
 :
 
 <ul>
 <li>
 Proficient in Python programming and libraries like NumPy, Pandas, Scikit-learn, and Matplotlib.
 </li>
 <li>
 Strong understanding of machine learning algorithms, deep learning architectures, and generative AI models.
 </li>
 <li>
 Design, develop, and deploy classical machine learning models, including supervised, unsupervised, and reinforcement learningtechniques.
 </li>
 <li>
 Hands on Experience in AI/ML Framework like: Scikit-learn, XG Boost, TensorFlow, Py Torch, Keras, Hugging Face, OpenAI APIs (e.g., GPT models).
 </li>
 <li>
 Experience with feature engineering, model evaluation, and hyperparameter tuning.
 </li>
 <li>
 Experience with Lang Chain modules, including Chains, Memory, Tools, and Agents.
 </li>
 <li>
 Build and fine-tune generative AI models (e.g., GPT, DALL-E, Stable Diffusion) for specific use cases.
 </li>
 <li>
 Must Have Exp. in any Agentic AI framework. Leverage LLMs (e.g., GPT, Claude, LLaMA) and multi-modal models to build intelligent agents that can interact with users and systems.
 </li>
 <li>
 Design and develop autonomous AI agents capable of reasoning, planning, and executing tasks in dynamic environments.
 </li>
 <li>
 Implement prompt engineering and fine-tuning of LLMs to optimize agent behaviour for specific tasks.
 </li>
 <li>
 Optimize models for performance, scalability, and cost-efficiency.
 </li>
 </ul>
 
 
 
 
 
 ML Ops and DevOps for AI/ML:
 
 
 <ul>
 <li>
 Establish and maintain an end-to-end MLOps pipeline for model development, deployment, monitoring, and retraining.
 </li>
 <li>
 Automate model training, testing, and deployment workflows using CI/CD pipelines.
 </li>
 <li>
 Implement robust version control for datasets, models, and code.
 </li>
 <li>
 Monitor model performance in production and implement feedback loops for continuous improvement.
 </li>
 <li>
 Proficiency in MLOps tools and platforms such as MLflow, Kubeflow, TFX, SageMaker.
 </li>
 <li>
 Familiarity with CI/CD tools like Jenkins, GitHub Actions, or GitLab CI for AI/ML workflows.
 </li>
 <li>
 Expertise in deploying models on cloud platforms (AWS, Azure, GCP)
 </li>
 </ul>
 
 
 
 
 
 RAKUTEN SHUGI PRINCIPLES
 
 :
 
 
 Our worldwide practices describe specific behaviours that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.
 
 
 
 Always improve, always advance
 
 . Only be satisfied with complete success - Kaizen.
 
 
 
 Be passionately professional
 
 . Take an uncompromising approach to your work and be determined to be the best.
 
 
 
 Hypothesize - Practice - Validate - Shikumika
 
 . Use the Rakuten Cycle to success in unknown territory.
 
 
 
 Maximize Customer Satisfaction
 
 . The greatest satisfaction for workers in a service industry is to see their customers smile.
 
 
 
 Speed!! Speed!! Speed!!
 
 Always be conscious of time. Take charge, set clear goals, and engage your team.
 
</div>

Data Scientist

eBay

<div>
 
 At eBay, we're more than a global ecommerce leader &mdash; we&rsquo;re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We&rsquo;re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
 
 
 Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work &mdash; every day. We're in this together, sustaining the future of our customers, our company, and our planet.
 
 
 Join a team of passionate thinkers, innovators, and dreamers &mdash; and help us connect people and build communities to create economic opportunity for all.
 
 
 
 
 
 
 Machine Learning Engineer
 
 
 
 
 
 
 
 Job Description
 
 
 
 The Compliance Engineering team at eBay is focused on prohibited, restricted, and counterfeit compliance detection is dedicated to ensuring that eBay&rsquo;s marketplace adheres to all relevant regulations and internal policies.
 
 
 The team develops and maintain advanced, AI-driven tools and scalable backend systems that automatically identify and assess items listed on the platform. By applying sophisticated data models, machine learning algorithms, and rules-based engines, they detect products that may be illegal, harmful, non-compliant with trade regulations, or counterfeit.
 
 
 Overall, this Compliance Engineering team plays a crucial role in maintaining trust in eBay&rsquo;s platform, safeguarding customers, and upholding the company&rsquo;s dedication to a fair, safe, and legally compliant marketplace.
 
 
 
 
 
 
 What You Will Accomplish:
 
 
 <ul>
 <li>
 Build large-scale applications, low-latency APIs, data pipelines, and foundational architectures to support eBay&rsquo;s business operations and customer experiences.
 </li>
 <li>
 Design and deploy high-performance APIs and data pipelines that seamlessly integrate machine learning models to extract valuable insights
 </li>
 <li>
 Design and implement highly configurable, metadata-driven platforms to enable seamless ingestion of attributes, rules, models, policies, and derived aggregates.
 </li>
 <li>
 Develop machine learning models and Gen AI tools to generate insights and improve customer experiences across eBay.
 </li>
 <li>
 Partner with architects, business leaders, and industry experts to devise strategies and scalable solutions.
 </li>
 <li>
 Be responsible for the entire software lifecycle, including design, development, testing, and experimentation.
 </li>
 <li>
 Foster a collaborative team environment by mentoring junior members, guiding them through projects to achieve transformed outcomes.
 </li>
 </ul>
 
 
 
 
 
 What You Will Bring:
 
 
 <ul>
 <li>
 Prefer Technical degree with 6-8+ years of relevant software development experience.
 </li>
 <li>
 Strong hands on Machine Leaning experience, AI/ML/Gen AI, LLM's and proven experience in building and running AI/ML/GenAI models in production environments.
 </li>
 <li>
 Outstanding programming skills in Java, Scala, and Python, with hands-on experience in frameworks like PyTorch and TensorFlow.
 </li>
 <li>
 Demonstrated experience in applying AI/ML techniques to build and run models in production environments.
 </li>
 <li>
 Proven experience with APIs and Distributed Systems, building and consuming horizontally scalable RESTful APIs, GraphQL, and distributed systems.
 </li>
 <li>
 Hands-on experience with technologies like Spark, Flink, and Kafka with practical experience in their use.
 </li>
 <li>
 Strong understanding of SQL, NoSQL, and sophisticated data modeling techniques.
 </li>
 <li>
 Hands-on experience with the Hadoop ecosystem (HDFS, MapReduce, Hive, Spark) for building and optimizing large-scale data solutions.
 </li>
 <li>
 Strong data modeling skills, encompassing both SQL and NoSQL environments
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer

Psyche Graphics W.L.L. Bahrain

<div>
 
 About Us
 
 
 
 Mercari is a Japan-based C2C marketplace company founded in 2013 with the mission to "Create value in a global marketplace where anyone can buy &amp; sell." From being the first tech unicorn from Japan before its IPO in 2018 we have come a long way towards becoming a global player and continuously and diligently work towards our transformation journey with a strong focus on our mission.
 
 
 Since its inception, Mercari Group has worked to grow its services, investing in both our people and technology. Over time Mercari has expanded from being the top player in the C2C marketplace in Japan to new geographies like the U.S. We have also successfully launched new businesses such as Merpay, which is a mobile payment service platform with a vision to create a society where anyone can realize their dreams through a new ecosystem centered not only on payment service but also on credit. Today, Mercari Group is made up of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management.
 
 
 For our services to be utilized by people worldwide; however, there is still a mountain of work ahead of us. This endeavor naturally requires the capability of the best talent and minds, and that is exactly the reason for us to launch the India Center of Excellence. With your help, we will continue to take on the world stage and strive to grow into a successful global tech company.
 
 
 
 Our Culture
 
 
 
 To achieve our mission at Mercari, our organization and each of our employees share the same values and perspectives. Our individual guidelines for action are defined by our four values: Go Bold, All for One, Be a Pro and Move Fast. Our organization is also shaped by our four foundations: Sustainability, Diversity &amp; Inclusion, Trust &amp; Openness, and Well-being for Performance. Regardless of how big Mercari gets, the culture will remain essential to achieving our mission and something we want to preserve throughout our organization. We invite you to read the Mercari Culture Doc which summarizes the behaviors and mindset shared by Mercari and its employees. We continue to build an environment where all of our members of diverse backgrounds are accepted and recognized, and where they can thrive while holding dear to Mercari's culture.
 
 
 
 Work Responsibilities
 
 
 
 As an AI Engineer in our new AI Taskforce team, you will be at the forefront of designing, developing, and deploying innovative AI applications using foundation models (e.g., Large Language Models, Multimodal Models) across Mercari. You will build foundational platforms and services that empower product teams to ship robust, scalable AI-powered features. This role is crucial for bridging the gap between cutting-edge research and production systems that deliver measurable value to millions of users, directly contributing to our mission to "Create value in a global marketplace where anyone can buy &amp; sell."
 
 
 
 Bold Challenges
 
 
 
 <ul>
 <li>
 Build Foundational AI Services: Design, build, and deploy core generative AI applications and services using modern techniques like prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning to solve high-impact problems across the Mercari ecosystem
 </li>
 <li>
 Drive AI Adoption: Collaborate closely with product, engineering, and infrastructure teams to integrate powerful AI capabilities into the Mercari app, architecting modular and scalable solutions that other teams can build upon
 </li>
 <li>
 Ensure AI Quality and Safety: Develop and champion robust evaluation pipelines to rigorously measure, monitor, and improve model performance, focusing on accuracy, latency, cost, and responsible AI principles
 </li>
 <li>
 Lead the Full AI Lifecycle: Own features end-to-end, from problem scoping and prototyping to production deployment, maintenance, and iteration based on quantitative metrics and qualitative user feedback
 </li>
 <li>
 Innovate and Educate: Be a key technical voice on our new central team. Stay at the forefront of advancements in AI engineering and share your knowledge to help uplift the technical capabilities of the entire organization
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Minimum Requirements
 
 
 
 <ul>
 <li>
 2-6 years of professional software engineering experience, with a demonstrated focus on building and deploying AI/ML-powered systems in production
 </li>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, or a related field
 </li>
 <li>
 Proficiency in Python and hands-on experience building applications with Large Language Models (LLMs) and familiarity with core concepts such as prompt engineering, RAG, and fine-tuning
 </li>
 <li>
 Experience building Model Context Protocol(MCP) servers in either Python or Go
 </li>
 <li>
 Solid understanding of software engineering fundamentals and the ability to write clean, maintainable, and production-ready code
 </li>
 <li>
 Strong problem-solving skills and a data-driven approach to decision-making
 </li>
 <li>
 Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders across multiple teams.
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 
 
 <ul>
 <li>
 Experience designing and implementing systematic evaluation strategies for generative AI systems (e.g., AI-as-judge, human-in-the-loop)
 </li>
 <li>
 Experience with cloud platforms (GCP, AWS, etc.) and containerization technologies (Docker, Kubernetes)
 </li>
 <li>
 Contributions to open-source projects or publications in top-tier AI/ML conferences
 </li>
 <li>
 Experience with microservice architecture and development
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Employment Status: Full-time
 </li>
 <li>
 Office: Bangalore
 </li>
 <li>
 Hybrid workstyle: We believe in high performance and professionalism. We work from the office 2 days/week and work from home 3 days/week
 </li>
 <ul>
 <li>
 To build a strong &amp; highly-engaged organization in India, we highly encourage everyone to work from our Bangalore office, especially during the initial office setup phase
 </li>
 <li>
 We will continue to review and update the policy to address future organizational needs
 </li>
 </ul>
 <li>
 Work Hours: Full flextime (no core time)
 </li>
 <ul>
 <li>
 Flexible to choose working hours other than team common meetings
 </li>
 </ul>
 </ul>
</div>

AI Engineer

Microsoft

<div>
 Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft&rsquo;s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers&rsquo; heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.
 
 
 The Defender Experts (DEX) Research team is at the forefront of Microsoft&rsquo;s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left&mdash;disrupting threats early, before damage occurs&mdash;by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We&rsquo;re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX&rsquo;s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter&mdash;with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you.
 
 
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions.
 </li>
 <li>
 Design and build robust, large-scale graph structures to model security entities, behaviors, and relationships.
 </li>
 <li>
 Develop and deploy scalable, production-grade AI/ML systems and intelligent agents for real-time threat detection, classification, and response.
 </li>
 <li>
 Collaborate closely with Security Research teams to integrate domain knowledge into data science workflows and enrich model development.
 </li>
 <li>
 Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment.
 </li>
 <li>
 Work with large-scale graph data: create, query, and process it efficiently to extract insights and power models.
 </li>
 <li>
 Lead initiatives involving Graph ML, Generative AI, and agent-based systems, driving innovation across threat detection, risk propagation, and incident response.
 </li>
 <li>
 Collaborate closely with engineering and product teams to integrate solutions into production platforms.
 </li>
 <li>
 Mentor junior team members and contribute to strategic decisions around model architecture, evaluation, and deployment.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field
 </li>
 <li>
 6+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection
 </li>
 <li>
 Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn)
 </li>
 <li>
 Strong foundation in statistics, probability, and applied machine learning techniques
 </li>
 <li>
 Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams
 </li>
 <li>
 Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end
 
 
 </li>
 </ul>
 Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
</div>

Senior Applied & Data scientist

LinkedIn

<div>
 
 Company Description
 
 
 
 LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.
 
 
 
 Job Description
 
 
 
 We are looking for an Staff Machine Learning Engineer to play a pivotal role as a technical leader within the LSS AI team. This role goes beyond building models- you will set the technical direction, own the AI roadmap, and lead initiatives that push the boundaries of what's possible in enterprise AI. You will combine deep research expertise with the ability to build production-grade ML systems at scale, partnering across engineering, product, and research to deliver transformative AI solutions.
 
 
 At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Lead the design, development, and deployment of state-of-the-art ML systems across search, recommendations, generative AI, reinforcement learning, and LLMs for Sales Navigator.
 </li>
 <li>
 Define and drive the technical roadmap and architecture for end-to-end AI systems within LSS, ensuring scalability, reliability, and innovation.
 </li>
 <li>
 Research, fine-tune, and adapt large language models (LLMs) and build agentic AI systems that enable reasoning, planning, and decision-making for sales professionals.
 </li>
 <li>
 Partner with product, design, and other engineering teams to align AI solutions with business strategy and maximize impact.
 </li>
 <li>
 Drive cross-functional collaborations with horizontal AI and platform teams to leverage foundational tools and scale adoption of innovations across LinkedIn.
 </li>
 <li>
 Mentor and guide engineers, fostering a culture of craftsmanship, innovation, and technical excellence.
 </li>
 <li>
 Represent LinkedIn in external venues (papers, conferences, workshops) by showcasing advances in applied AI research and engineering.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Basic Qualifications
 
 
 <ul>
 <li>
 MS/PhD degree in Computer Science or related technical discipline, or equivalent practical experience.
 </li>
 <li>
 8+ years of experience in machine learning, artificial intelligence, or related fields.
 </li>
 <li>
 5+ years in an architect or technical leadership role driving large-scale AI initiatives.
 </li>
 <li>
 Hands-on experience with end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and optimization.
 </li>
 <li>
 Expertise in at least one of: LLMs, generative AI, search/recommendations, reinforcement learning, or large-scale deep learning.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 10+ years of experience building and scaling machine learning systems in production.
 </li>
 <li>
 Proven experience in pre-training and fine-tuning LLMs, including domain-specific adaptations.
 </li>
 <li>
 Strong software engineering skills (Python, Java, C++, or similar), with the ability to design robust, scalable systems.
 </li>
 <li>
 Track record of influencing product and technical strategy through AI/ML innovation.
 </li>
 <li>
 Publications, patents, or open-source contributions in machine learning, NLP, or related areas.
 
 
 
 </li>
 </ul>
 Suggested Skills
 
 
 <ul>
 <li>
 Machine Learning
 </li>
 <li>
 Large Language Models
 </li>
 <li>
 Generative AI
 </li>
 <li>
 Search &amp; Recommendations
 </li>
 <li>
 Reinforcement Learning
 </li>
 <li>
 Technical Leadership
 </li>
 <li>
 Cross-Functional Collaboration
 
 
 
 </li>
 </ul>
 You Will Benefit from Our Culture
 
 
 We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
 
 
 
 Additional Information
 
 
 
 
 India Disability Policy
 
 
 
 LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
 
 
 
 Global Data Privacy Notice for Job Candidates
 
 
 
 Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
 
 
</div>

Staff Software Engineer, Machine Learning

symplr

<div>
 We are looking for a highly motivated
 
 SDET
 
 to join our team and ensure the quality and reliability of applications that incorporate
 
 AI/ML components
 
 . This role demands strong skills in
 
 automated testing, using
 
 scripting like Python,
 
 TypeScript
 
 , and hands-on experience with
 
 cloud infrastructure (preferably AWS)
 
 . Exposure with solutions built using AI/ML/GenAI is a key advantage.
 
 
 
 Duties &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design and implement automated test suites for web and backend systems using any scripting language, preferably python or typescript.
 </li>
 <li>
 Expert in developing AI/ML solutions using python
 </li>
 <li>
 Work closely with development, ML, and DevOps teams to test features powered by AI/ML models.
 </li>
 <li>
 Validate ML model predictions, data inputs/outputs, and model integration with application logic.
 </li>
 <li>
 Build and maintain test infrastructure on AWS, including test environments, CI/CD pipelines, and test execution in cloud-based containers.
 </li>
 <li>
 Participate in code reviews and pair programming for quality gatekeeping.
 
 
 </li>
 </ul>
 
 Skills Required
 
 
 
 <ul>
 <li>
 5&ndash;8 years of experience in a Development or QE Automation or SDET role.
 </li>
 <li>
 Strong hands-on experience using AI/ML models and python or typescript for test automation.
 </li>
 <li>
 Strong experience in prompt engineering
 </li>
 <li>
 Experience working in AWS environments, including EC2, S3, Lambda, or CloudWatch.
 </li>
 <li>
 Experience working with AWS Bedrock, Claud LLM or SLM&rsquo;s
 </li>
 <li>
 Familiarity with AI/ML model integration and understanding of the basics of model behavior, metrics, and quality concerns.
 </li>
 <li>
 Experience with REST API testing, JSON, and HTTP protocols.
 </li>
 <li>
 Working knowledge of CI/CD pipelines (e.g., GitHub Actions, Jenkins, CodePipeline).
 </li>
 <li>
 Understanding of software testing principles and test-driven development.
 </li>
 <li>
 Excellent communication and collaboration skills.
 </li>
 </ul>
</div>

Software Engineer

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