Responsibilities Screen resumes as per job descriptions. Scheduling interviews. Source candidates by using databases, social network media, cold calling, etc. Coordinate interviews with the technical panel. Mandatory regular reports on hiring status. Perform reference and background Checks. Maintain accurate and up-to-date candidate information in our recruiting database. Joining and Induction formalities. HR Generalist activities. Making recommendations to company hiring managers. Communicating employer information and benefits during the screening process. Requirements Experience in IT recruitment. Should possess a qualification in MBA (HR). Candidate should possess excellent communication skills (Written and Verbal). Knowledge about HR Activities / HRBP/ Recruitment / Administration, etc. Team player with a positive attitude. This job was posted by Careers Softility from Softility. Show more Show less
We are seeking a Data Scientist with a strong background in enterprise-scale machine learning, deep expertise in LLMs and Generative AI, and a clear understanding of the evolving Agentic AI ecosystemThe ideal candidate has hands-on experience developing predictive models, recommendation systems, and LLM-powered solutions, and is passionate about leveraging cutting-edge AI to solve complex enterprise challenges. This role will involve working closely with product, engineering, and business teams to design, build, and deploy impactful AI solutions that are both technically robust and business-aligned. The Core Responsibilities For The Job Include The Following ML and Predictive Systems Development: Design, develop, and deploy enterprise-grade machine learning models for recommendations, predictions, and personalization use cases. Work on problems such as churn prediction, intelligent routing, anomaly detection, and behavior modeling. Leverage techniques in supervised, unsupervised, and reinforcement learning as needed based on business context. LLMs And Generative AI Build and fine-tune LLM-based solutions (e. g., GPT, LLaMA, Claude, or open-source models) for tasks such as summarization, semantic search, document understanding, and copilots. Deliver production-ready GenAI projects, applying techniques like RAG (Retrieval-Augmented Generation), prompt engineering, fine-tuning, and vector search (e. g., FAISS, Pinecone, Weaviate). Collaborate with engineering to embed LLM workflows into enterprise applications, ensuring scalability and performance. Agentic AI And Ecosystem Engagement Contribute thought leadership and experimentation around Agentic AI architectures, task orchestration, memory management, tool integration, and decision autonomy. Stay ahead of trends in the open-source and commercial LLM/AI space, including LangChain, AutoGen, DSPy, and ADK-based systems. Develop internal PoCs or evaluate frameworks to assess viability for enterprise use. Collaboration And Delivery Work with cross-functional teams to identify AI opportunities and define technical roadmaps. Translate business needs into data science problems, define success metrics, and communicate results to stakeholders. Ensure model governance, monitoring, and explainability for AI systems in production. Requirements Master's or PhD in Computer Science, Data Science, Statistics, or related field. 5-8 years of experience in data science and ML, with strong enterprise project delivery experience. Proven success in building and deploying ML models and recommendation systems at scale. 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, LangChain, Vector DBs, or model fine-tuning. Advanced Python programming skills and experience with ML libraries (e. g., Scikit-learn, XGBoost, PyTorch, TensorFlow). Experience with cloud-based ML/AI platforms (e. g., Vertex AI, AWS SageMaker, Azure ML). Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, CrewAI). Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. Working knowledge of MLOps best practices, including model versioning, CI/CD for ML, and model monitoring. Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Regular follower of AI research, open-source trends, and GenAI product developments. This job was posted by Akshay Kumar Arumulla from Softility.
Requirements Experience with Data Transfer tools and methods, including the ability to create and process change requests for new and existing clients related to: GlobalScape NDM (including Secure+) AWS S3/ AWS CLI GCP Azure Blob WinSCP/Putty Experience with certificate management/ application License management. Experience with server patching and maintenance, vulnerability remediation, and Server. Monitoring/ system diagnostic tools/ maintenance reports (Rapid7 Brinqa). Experience with File server management. Experience in Active Directory & amp; DNS management. Extensive knowledge of AWS Services: Including but not limited to VPC, EC2 EMR, S3 Fargate, and Load balancers. EFX, EBS, AWS workspaces. The Ability to install and configure the software in accordance with installation procedures, organizational guidelines, and plans. System configuration, default user settings, etc. Experience with managing server access requests/ system accounts/ password management. Experience managing Instance/EBS snapshots. Experience with server decommissions. Experience with change control processes (presenting use cases, changes, testing, approvals, etc. ) Experience with setup and configuration of user tools (Dbeaver, Excel Macro functionality, Vedit, etc. ) and troubleshooting. This job was posted by Hymavati Sarojini from Softility.
You should have experience with Data Transfer tools and methods, including the ability to create and process change requests for new and existing clients. This includes expertise in GlobalScape, NDM (including Secure+), AWS S3/AWS CLI, GCP, Azure Blob, WinSCP/Putty. Additionally, you should have proficiency in certificate management and application license management. Experience with server patching, maintenance, vulnerability remediation, and server monitoring is essential. Familiarity with system diagnostic tools and maintenance reports such as Rapid7 and Brinqa is required. You should also possess expertise in file server management, Active Directory, and DNS management. Extensive knowledge of AWS services is a must, including VPC, EC2 EMR, S3 Fargate, Load balancers, EFX, EBS, AWS Workspaces. You should be able to install and configure software according to organizational guidelines and plans, including system configuration and default user settings. Managing server access requests, system accounts, password management, Instance/EBS snapshots, server decommissions, and change control processes will be part of your responsibilities. You should also have experience in setting up and configuring user tools like Dbeaver, Excel Macro functionality, Vedit, and troubleshooting any related issues. This position was posted by Hymavati Sarojini from Softility.,
Job Title: Data Scientist ML, GenAI & Agentic AI Position Summary We are seeking a Data Scientist with a strong background in enterprise-scale machine learning , deep expertise in LLMs and Generative AI , and a clear understanding of the evolving Agentic AI ecosystem . The ideal candidate has hands-on experience developing predictive models, recommendation systems, and LLM-powered solutions, and is passionate about leveraging cutting-edge AI to solve complex enterprise challenges. This role will involve working closely with product, engineering, and business teams to design, build, and deploy impactful AI solutions that are both technically robust and business-aligned. Key Responsibilities ML & Predictive Systems Development Design, develop, and deploy enterprise-grade machine learning models for recommendations, predictions, and personalization use cases. Work on problems such as churn prediction, intelligent routing, anomaly detection, and behavior modeling. Leverage techniques in supervised, unsupervised, and reinforcement learning as needed based on business context. LLMs & Generative AI Build and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, or open-source models) for tasks such as summarization, semantic search, document understanding, and copilots. Deliver production-ready GenAI projects, applying techniques like RAG (Retrieval-Augmented Generation), prompt engineering, fine-tuning, and vector search (e.g., FAISS, Pinecone, Weaviate). Collaborate with engineering to embed LLM workflows into enterprise applications, ensuring scalability and performance. Agentic AI & Ecosystem Engagement Contribute thought leadership and experimentation around Agentic AI architectures, task orchestration, memory management, tool integration, and decision autonomy. Stay ahead of trends in the open-source and commercial LLM/AI space, including LangChain, AutoGen, DSPy, and ADK-based systems. Develop internal PoCs or evaluate frameworks to assess viability for enterprise use. Collaboration & Delivery Work with cross-functional teams to identify AI opportunities and define technical roadmaps. Translate business needs into data science problems, define success metrics, and communicate results to stakeholders. Ensure model governance, monitoring, and explainability for AI systems in production. Required Qualifications Masters or PhD in Computer Science, Data Science, Statistics, or related field. 58 years of experience in data science and ML, with strong enterprise project delivery experience. Proven success in building and deploying ML models and recommendation systems at scale. 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, LangChain, Vector DBs, or model fine-tuning. Advanced Python programming skills and experience with ML libraries (e.g., Scikit-learn, XGBoost, PyTorch, TensorFlow). Experience with cloud-based ML/AI platforms (e.g., Vertex AI, AWS SageMaker, Azure ML). Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, CrewAI). Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. Working knowledge of MLOps best practices including model versioning, CI/CD for ML, and model monitoring. Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Regular follower of AI research, open-source trends, and GenAI product developments.
Company Description Softility is a digital transformation technology services company specializing in innovative solutions across cloud adoption and modernization, data engineering and analytics, AI-driven operations, digital service management, and cybersecurity. Based in Herndon, Virginia, USA, with an Innovation & Development Center in Hyderabad, India, we serve numerous large organizations, including Fortune 500 telecom companies, SLED entities, healthcare institutions, major enterprises, and federal government agencies. Our dynamic team of highly skilled engineers, guided by a seasoned leadership with over two decades of experience, is dedicated to delivering cutting-edge solutions that enable our customers to #BeFutureReady. Role Description This is a full-time, on-site role for a Big Data Developer, located in Hyderabad. The Big Data Developer will be responsible for designing, developing, and optimizing big data solutions. Day-to-day tasks include working on data engineering projects, performing ETL processes, managing data warehousing, and developing software solutions. The role also involves collaboration with cross-functional teams to ensure the effective implementation of data-driven solutions. Big Data Developer ● Participate in the design and implementation phases for data projects to help translate high level business requirements into technical solutions ● Provide technically sound solutions for the ingestion, storage, transformation, and presentation of enterprise data, including ETL design, data storage strategies, data access and security ● Driving the design of scalable solutions while considering recoverable and resiliency requirements ● Participate in DevOps related activities, including involvement with continuous integration, automated deployment, automated testing, and continuous monitoring to enhance performance and product quality ● Provide timely support for troubleshooting and resolving production issues Required Technical and Professional Expertise ● Experience with any of the following: Big Data technologies, Analytics, Hadoop ecosystems, Data Lakes, or Data Migration ● Experience with cloud platforms such as AWS, Azure, or Google Cloud ● Experience with Java, Scala, Spark ● Strong database integration and management skills ● Strong ETL skills, including database performance tuning and optimization ● Familiar with Shell scripting skills and Unix/Linux knowledge ● Exceptional analytical and problem-solving skills ● Running diagnostic tests and performing debugging procedures ● Documenting application development processes, procedures, and standards ● Excellent leadership and interpersonal skills ● Strong communication and team working skills ● Able to analyze complex situations and derive workable actions ● Flexibility to adjust to multiple demands, shifting priorities, ambiguity and rapid change Preferred Technical And Professional Expertise ● Knowledge of DevOps and related tooling such as Jenkins, Ansible etc. ● Experience with Big Data technologies such as Apache Hadoop, HBase, Hive, Spark, Flink or Flume ● Strong coding skills in one of Python/Java/Scala ● Familiar with event management technologies such as Apache Kafka or Apache Airflow ● Familiar with container technologies such as Docker or Kubernetes ● Demonstrable experience coaching junior members of your teams
Role Overview: As a Senior UX/UI Designer specializing in Design Systems & Front-End, you will be responsible for leading the maintenance, enhancement, and strategic modernization of the core data visualization platform. Your role will involve supporting existing AngularJS features while spearheading the re-architecture and migration of key components to modern Angular. Your primary focus will be on transforming raw telemetry data into intuitive, high-performance dashboards to ensure a seamless user experience across both legacy and modernized parts of the application. Key Responsibilities: - Maintain and enhance responsive user interfaces built with AngularJS (v1.x), HTML5, and modern CSS. - Support and improve the existing library of reusable AngularJS components and directives for displaying complex telemetry data. - Take ownership of optimizing the performance and stability of the existing event summary view. - Architect and implement efficient, low-latency API communication between front-end (Angular and AngularJS) and back-end services. - Develop and consume RESTful APIs providing aggregated and paginated data optimized for front-end rendering. - Lead the design and execution of a strategy to migrate the application from AngularJS to modern Angular. - Rearchitect legacy AngularJS components into well-structured, performant, and reusable modern Angular components. - Collaborate with the engineering team to make key architectural decisions for the application's future. - Ensure all new feature development follows best practices using modern Angular. Qualifications Required: - Portfolio showcasing work on design systems, UI component libraries, and detailed case studies demonstrating the design process. - Expert proficiency in modern design and prototyping tools such as Figma, Sketch, Adobe XD. - Strong, hands-on proficiency in front-end development technologies like HTML5. - Deep understanding of user-centered design principles, usability heuristics, and interaction design. - Experience with component-based JavaScript frameworks like Angular, React, or Vue.js. - Familiarity with web accessibility standards (WCAG) and application. - Experience in designing data-intensive applications and conducting user research for design improvements.,
We are seeking a Data Scientist with a strong background in enterprise-scale machine learning, deep expertise in LLMs and Generative AI, and a clear understanding of the evolving Agentic AI ecosystemThe ideal candidate has hands-on experience developing predictive models, recommendation systems, and LLM-powered solutions, and is passionate about leveraging cutting-edge AI to solve complex enterprise challenges. This role will involve working closely with product, engineering, and business teams to design, build, and deploy impactful AI solutions that are both technically robust and business-aligned. The Core Responsibilities For The Job Include The Following ML and Predictive Systems Development: Design, develop, and deploy enterprise-grade machine learning models for recommendations, predictions, and personalization use cases. Work on problems such as churn prediction, intelligent routing, anomaly detection, and behavior modeling. Leverage techniques in supervised, unsupervised, and reinforcement learning as needed based on business context. LLMs And Generative AI Build and fine-tune LLM-based solutions (e. g., GPT, LLaMA, Claude, or open-source models) for tasks such as summarization, semantic search, document understanding, and copilots. Deliver production-ready GenAI projects, applying techniques like RAG (Retrieval-Augmented Generation), prompt engineering, fine-tuning, and vector search (e. g., FAISS, Pinecone, Weaviate). Collaborate with engineering to embed LLM workflows into enterprise applications, ensuring scalability and performance. Agentic AI And Ecosystem Engagement Contribute thought leadership and experimentation around Agentic AI architectures, task orchestration, memory management, tool integration, and decision autonomy. Stay ahead of trends in the open-source and commercial LLM/AI space, including LangChain, AutoGen, DSPy, and ADK-based systems. Develop internal PoCs or evaluate frameworks to assess viability for enterprise use. Collaboration And Delivery Work with cross-functional teams to identify AI opportunities and define technical roadmaps. Translate business needs into data science problems, define success metrics, and communicate results to stakeholders. Ensure model governance, monitoring, and explainability for AI systems in production. Requirements Master's or PhD in Computer Science, Data Science, Statistics, or related field. 5-8 years of experience in data science and ML, with strong enterprise project delivery experience. Proven success in building and deploying ML models and recommendation systems at scale. 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, LangChain, Vector DBs, or model fine-tuning. Advanced Python programming skills and experience with ML libraries (e. g., Scikit-learn, XGBoost, PyTorch, TensorFlow). Experience with cloud-based ML/AI platforms (e. g., Vertex AI, AWS SageMaker, Azure ML). Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, CrewAI). Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. Working knowledge of MLOps best practices, including model versioning, CI/CD for ML, and model monitoring. Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Regular follower of AI research, open-source trends, and GenAI product developments. This job was posted by Akshay Kumar Arumulla from Softility.