AIOps Engineer - Data Science & Machine Learning

JOB RESPONSIBILITIES :- Assist in design and deployment of AI/ML solutions, ensuring alignment with business goals and technical requirements.- Collaborate with service and solution owners, technical & application teams to gather requirements, identify use cases, and propose solutions.- Create detailed technical solutions, including system architecture, data flow, and integration points.- Integrations with monitoring tools for metrics, logs and traces across infra, app, security, network domains- Integration with tools such as AppDynamics, New Relic, Splunk, Azure Log Analytics, SCOM, ServiceNow and RunDeck etc.- Implement scalable, efficient, and robust AI models, algorithms, and systems.- Collaborate with service and solution owners, technical, and non-technical teams to collect, clean, and prepare data for AI model training and evaluation.- Develop and maintain best practices and coding standards for AI solution development.- Troubleshoot and resolve technical issues related to AI systems.- Foster a culture of knowledge sharing and growth.- Create content (Docs, workflow diagrams, testing plans, training) related to specific use cases or best practices.- Provide training and guidance, as needed.- Monitor AIOps dashboards for Continual Improvement Opportunities.- Provide regular KPI and Metric updates including findings and adoption rates to leadership, escalating concerns as appropriate.- Stay up-to-date on advancements in AI technologies and research to drive innovation and continuous improvement.- Collaborate with Incident and Problem Management to reduce MTTR and Incident volume.- Design, implement, and maintain AIOps solutions to monitor and analyze IT systems, applications, and networks.- Deploy machine learning algorithms for anomaly detection, root cause analysis, and incident prediction.- Configure and manage observability tools and platforms to gain real-time visibility into system health and performance.- Develop monitoring dashboards, alerts, and reports to provide comprehensive insights into the IT environment.- Conduct root cause analysis for incidents using data from AIOps and observability tools to identify underlying issues.- Work closely with software engineers to instrument applications with appropriate logging, metrics, and tracing capabilities- Continuously analyze monitoring data to identify trends, anomalies, and opportunities for optimization.- Stay updated with industry trends and advancements in AIOps and observability practices, and recommend new tools or methodologies for adoption- Designing, developing, and implementing AI models and algorithms utilizing state-of-the-art techniques such as GPT, VAE, and GANs.- Collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.- Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.- Optimizing existing generative AI models for improved performance, scalability, and efficiency.- Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation.- Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.- Contributing to the establishment of best practices and standards for generative AI development within the organization.- Providing technical mentorship and guidance to junior team members.- Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems- Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI- Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines- Implement monitoring and logging tools to ensure AI model performance and reliability- Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.- Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.KEY QUALIFICATION & EXPERIENCES :- Minimum 5 years of experience in Data Science and Machine Learning- Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.- 8+ years of industry experience in software development.- Strong proficiency in Java, Spring Boot, REST Web Services, Kafka, and Microservices architecture.- Strong understanding of object-oriented programming principles and design patterns.- Experience with AIOps and machine learning is highly desirable.- Knowledge of OpenTelemetry is an added advantage.- Experience with other monitoring tools like Prometheus, Grafana, etc.- Experience with Observability solutions like Dynatrace, DataDog, Instana etc. is highly desirable- Experience working with mainframe systems is a plus (willingness to learn is also acceptable).- Excellent problem-solving and analytical skills.- Strong communication and collaboration skills.- Ability to work independently and manage multiple projects simultaneously.- Passion for learning new technologies and continuous improvement.- In-depth knowledge of machine learning, deep learning, and generative AI techniques- Knowledge and experience in Generative AI- Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch- Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models- Familiarity with computer vision techniques for image recognition, object detection, or image generation- Experience with cloud platforms such as Azure or AWS- Expertise in data engineering, including data curation, cleaning, and preprocessing- Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems- Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.- Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions- Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels- Track record of driving innovation and staying updated with the latest AI research and advancements- Knowledge of IT operations concepts and processes, such as monitoring, incident management, root cause analysis, remediation.- You have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.- You have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.- You are proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.- You have strong knowledge of data structures, algorithms, and software engineering principles.- You are familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.- You have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.- You are familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.- You have knowledge of software development methodologies, such as Agile or Scrum.- You possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.- You have strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.- You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment.- Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.- Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.- Certification - ITIL V3 / V4- Hands-on experience in Observability & AIOP tools (preferably SolarWinds, Moog soft, BigPanda, Splunk, Science Logic, Logic Monitor , New Relic, AppDynamics etc)- Experience in working with AI frameworks and tools, such as TensorFlow, PyTorch, Scikit-learnOTHER INFORMATION- Travel: as required.- Job is primarily performed in a Hybrid office environment.A Master degree is preferred. (ref:hirist.tech)