Behavioural Scientist

Job Title: Tutor or Assistant Professor – Cardiac Technology

Department: Cardiac Technology

Institution Type: KGiSL Educational Institution

Job Summary:

The Tutor or Assistant Professor – Cardiac Technology will be responsible for teaching undergraduate students, conducting practical and clinical training sessions, guiding academic projects, and supporting departmental academic and research activities. The candidate should possess strong theoretical and practical knowledge in cardiac diagnostic and therapeutic procedures.

Minimum Qualification:

B.Sc. in Cardiac Technology (or equivalent qualification in Cardiac Technology)

Minimum 2 years of relevant teaching or clinical experience

Key Responsibilities:

Deliver lectures and conduct practical sessions in cardiac technology subjects as per curriculum requirements.

Train students in ECG, TMT, Echocardiography, cardiac catheterization lab procedures, and other non-invasive and invasive cardiac diagnostic techniques.

Prepare lesson plans, teaching materials, and evaluation methods.

Supervise students during clinical postings and hospital training.

Assess student performance through internal assessments, practical examinations, and viva voce.

Maintain academic records, attendance registers, and examination documentation.

Participate in curriculum development and departmental planning activities.

Guide students in academic projects, case studies, and research activities.

Ensure proper maintenance and safe handling of cardiac diagnostic equipment.

Contribute to seminars, workshops, research publications, and institutional development activities.

Required Skills:

Strong knowledge of cardiovascular anatomy, physiology, and cardiac diagnostic procedures.

Proficiency in handling cardiac diagnostic equipment.

Effective teaching and presentation skills.

Good communication and interpersonal abilities.

Research aptitude and academic writing skills.

Basic computer proficiency (MS Office and academic software).

Preferred Attributes:

Experience in teaching within an educational institution.

Clinical exposure in reputed hospitals or cardiac centers.

Participation in professional development programs and conferences.

Job Description for Project Manager:

• Exposure to US/International Client (Preferred) Prior Experience in Digital Marketing (Search Engine Optimization) / Project Coordinator / Project Manager roles.
• Excellent written and verbal communication and presentation skills, able to generate interest and engage the client during calls and on emails.
• Manage projects, establish productive, professional, and profitable relationships with key personnel and clients in assigned projects.
• Coordinate with various departments within the organization, including support, service, technology, and manage resources, in order to ensure seamless functioning of the client accounts.
• Responsible for client receivables; planning and execution of monthly retention.
• Candidates with Project Management, Digital Marketing & Technical Skills Preferred.
• Document all requests and comments made by clients to ensure timely feedback and follow-up actions of client escalations/queries.
• Ability to maintain a positive, motivational, 'get things done' attitude, especially when faced with difficult circumstances.
• Achieves strategic customer objectives and account plans defined by company management.
• Good relationship-building skills (internal, external, and cross-cultural).
• Sound computer skills, especially in the areas of MS Word, MS Excel, and MS PowerPoint.
• Lead solution development efforts that best address customer needs, while coordinating the involvement of all necessary actions required and always keep the internal team updated.
• Maintain a consistent schedule of online meetings with the client to manage performance objectives, customer-expectations and assess customer needs on an ongoing basis.

What we are looking for-

• Excellent communication skills
• Must have enthusiasm and a sincere attitude.

Strong Data Scientist/Machine Learnings/ AI Engineer Profile

Mandatory (Experience 1) – Must have 2+ years of hands-on experience as a Data Scientist or Machine Learning Engineer building ML models

Mandatory (Experience 2) – Must have strong expertise in Python with the ability to implement classical ML algorithms including linear regression, logistic regression, decision trees, gradient boosting, etc.

Mandatory (Experience 3) – Must have hands-on experience in minimum 2+ usecaseds out of recommendation systems, image data, fraud/risk detection, price modelling, propensity models

Mandatory (Experience 4) – Must have strong exposure to NLP, including text generation or text classification (Text G), embeddings, similarity models, user profiling, and feature extraction from unstructured text

Mandatory (Experience 5) – Must have experience productionizing ML models through APIs/CI/CD/Docker and working on AWS or GCP environments

Mandatory (Company) – Must be from product companies, Avoid candidates from financial domains (e.g., JPMorgan, banks, fintech)

Job Description: 

Machine Learning / AI Engineer (with 3+ years of experience)

We are seeking a highly skilled and passionate Machine Learning / AI Engineer to join our newly established data science practice area. In this role, you will primarily focus on working with Large Language Models (LLMs) and contribute to building generative AI applications. This position offers an exciting opportunity to shape the future of AI technology while charting an interesting career path within our organization.

Responsibilities:

1. Develop and implement machine learning models: Utilize your expertise in machine learning and artificial intelligence to design, develop, and deploy cutting-edge models, with a particular emphasis on Large Language Models (LLMs). Apply your knowledge to solve complex problems and optimize performance.

2. Building generative AI applications: Collaborate with cross-functional teams to conceptualize, design, and build innovative generative AI applications. Work on projects that push the boundaries of AI technology and deliver impactful solutions to real-world problems.

3. Data preprocessing and analysis: Collect, clean, and preprocess large volumes of data for training and evaluation purposes. Conduct exploratory data analysis to gain insights and identify patterns that can enhance the performance of AI models.

4. Model training and evaluation: Develop robust training pipelines for machine learning models, incorporating best practices in model selection, feature engineering, and hyperparameter tuning. Evaluate model performance using appropriate metrics and iterate on the models to improve accuracy and efficiency.

5. Research and stay up to date: Keep abreast of the latest advancements in machine learning, natural language processing, and generative AI. Stay informed about industry trends, emerging techniques, and open-source libraries, and apply relevant findings to enhance the team's capabilities.

6. Collaborate and communicate effectively: Work closely with a multidisciplinary team of data scientists, software engineers, and domain experts to drive AI initiatives. Clearly communicate complex technical concepts and findings to both technical and non-technical stakeholders.

7. Experimentation and prototyping: Explore novel ideas, experiment with new algorithms, and prototype innovative solutions. Foster a culture of innovation and contribute to the continuous improvement of AI methodologies and practices within the organization.

Requirements:

1. Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Relevant certifications in machine learning, deep learning, or AI are a plus.

2. Experience: A minimum of 3+ years of professional experience as a Machine Learning / AI Engineer, with a proven track record of developing and deploying machine learning models in real-world applications.

3. Strong programming skills: Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, pandas). Experience with cloud platforms (e.g., AWS, Azure, GCP) for model deployment is preferred.

4. Deep-learning expertise: Strong understanding of deep learning architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and familiarity with Large Language Models (LLMs) such as GPT-3, GPT-4, or equivalent.

5. Natural Language Processing (NLP) knowledge: Familiarity with NLP techniques, including tokenization, word embeddings, named entity recognition, sentiment analysis, text classification, and language generation.

6. Data manipulation and preprocessing skills: Proficiency in data manipulation using SQL and experience with data preprocessing techniques (e.g., cleaning, normalization, feature engineering). Familiarity with big data tools (e.g., Spark) is a plus.

7. Problem-solving and analytical thinking: Strong analytical and problem-solving abilities, with a keen eye for detail. Demonstrated experience in translating complex business requirements into practical machine learning solutions.

8. Communication and collaboration: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse stakeholders

Hi,
Intuitive (http://www.intuitive.cloud/">www.intuitive.cloud) is one of the fastest-growing Cloud & SDx Engineering solution and services companies supporting 80+ Fortune 1000 Global Enterprise customers in the Americas and Europe. Intuitive is a recognized professional & managed services partner for core superpowers in Cloud (Public/Hybrid) Adoption/Migration & Transformation, Cloud Security, GRC, DevSecOps, SRE, Data, Application Modernization / Containers/K8s-as-a-Service and Cloud Application Delivery
FTE (permanent)
100% Remote opportunity 
Time-6 pm to 3.00 am(IST)
Role: Azure Network & Security Architect JD:

Must have:

Strong understanding of data center network and security architecture with products like Cisco switches/routers, Arista/juniper switches/routers, Palo Alto/Cisco/Fortinet firewalls, proxy, DNS etc Strong understanding of overall Azure cloud infrastructure, network and security architecture. In-depth understanding of Azure Networking components/services like vnet, vnet peering, udr, SDR, express route, NVA, load balancers, endpoints,vWAN, virtual Network gateways, Network watcher, Azure network function manager, CDN, Private link, traffic manager etc In-depth understanding of Azure Security components/services like Azure firewall, Azure firewall manager, Azure front door, WAF,  NSG, Internet analyzer, Bastion, Defender, Key Vault, Sentinel etc Strong understanding of how to securely interconnect multiple cloud accounts, on-prem servers, etc. Expertise in automation tools such as Terraform/Jenkins/Powershell/Ansible/Azure CLI etc. Strong understanding of How to protect Azure Cloud-based infrastructure, including distributed denial-of-service (DDoS) attacks, phishing attacks, and threats involved. content classification etc

Good to have: Sound understanding of GCP and AWS cloud network and security architecture Sound understanding of F5 load balancers/LTM/GTM, AFM, ASM, APM etc

If Your profile matches to the requirements share your anithadotkatintuitivedotcloud
Regards,
Anitha. K
TAG Specialist

Job Description for :

Role: Data/Integration Architect

Experience – 8-10 Years

Notice Period: Under 30 days

Key Responsibilities: Designing, Developing frameworks for batch and real time jobs on Talend. Leading migration of these jobs from Mulesoft to Talend, maintaining best practices for the team, conducting code reviews and demos.

Core Skillsets:

Talend Data Fabric - Application, API Integration, Data Integration. Knowledge on Talend Management Cloud, deployment and scheduling of jobs using TMC or Autosys.

Programming Languages - Python/Java
Databases: SQL Server, Other Databases, Hadoop

Should have worked on Agile

Sound communication skills

Should be open to learning new technologies based on business needs on the job

Additional Skills:

Awareness of other data/integration platforms like Mulesoft, Camel

Awareness Hadoop, Snowflake, S3