7 Shap Jobs

As the AI Model Development & Deployment Lead, your primary responsibility will be to design and implement cutting-edge computer vision models for various tasks such as object detection, tracking, segmentation, and action recognition. You should have expertise in architectures like YOLO (v4, v5, v8), Vision Transformers, Mask R-CNN, Faster R-CNN, LSTMs, and Spatio-Temporal Models for in-depth image and video analysis. It will be crucial to contextualize the models for challenging scenarios like poor detection due to occlusion or small, fast-moving objects by training them on diverse situations. Your role will involve identifying reasons for suboptimal model performance and developing a scalable computer vision layer adaptable to different environments. Collaborating with data scientists using frameworks like TensorFlow and Pytorch, you will drive impact across key KPIs and optimize models for real-time inference through techniques such as quantization, pruning, and model distillation. In the realm of Reinforcement Learning & Model Explainability, you will be tasked with developing and integrating reinforcement learning models to enhance decision-making in dynamic AI environments. This will involve working with Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), A3C, SAC, and other RL techniques. Furthermore, you will explore explainability methods such as SHAP, LIME, and Grad-CAM to ensure transparency and interpretability of AI-driven decisions. Additionally, engineering context-aware features from video sequences to extract temporal and spatial insights for improved model explainability and decision accuracy will be part of your responsibilities. Leading the charge in creating a Scalable Data Model for AI Model Training Pipelines, you will oversee the end-to-end data preparation process, including data gathering, annotation, and quality review before training data utilization. The focus will be on enhancing the quality and volume of training data continuously to boost model performance iteratively. Your expertise in planning the data model for future scalability, with the ability to incorporate new data elements in a modular manner, will be essential. Key Technical Skills required for this role include a proven track record in delivering AI products, hands-on experience with advanced AI models, proficiency in managing and mentoring a small team of data scientists, expertise in AI/ML frameworks like TensorFlow, PyTorch, and Keras, effective collaboration with cross-functional teams, and strong problem-solving skills in image and video processing challenges. Nice to have skills include a mindset for experimentation, iterative improvement, and testing to enhance model performance continually, staying updated with the latest AI research, and balancing experimentation with timely product delivery. Collaboration with engineering and product teams to align AI solutions with product goals and deployment of AI models into production are crucial aspects. Additionally, leadership in guiding and mentoring a team of AI scientists, taking ownership of product KPIs related to AI models, and fostering an AI-first culture focused on innovation and continuous improvement will be part of your role.,

Expertise in GenAI, deep learning frameworks (TensorFlow/PyTorch), Strong Python/R programming with experience in ML libraries, Proficiency in cross-validation strategies, bias-variance trade-off, model interpretability (SHAP, LIME), fairness metrics and all other performance metrics

Job Title: Security Architect - AI Products & Multi-Cloud Security Location : Offshore( Bangalore/Pune/Hyderabad) Job Summary We are seeking a skilled Security Architect to ensure the security of our AI-powered products across multi-cloud platforms. This role will focus on implementing end-to-end security practices during the entire software development lifecycle, ensuring data privacy, safeguarding AI models, and promoting Responsible AI practices. You will be instrumental in developing and enforcing security guardrails that protect our AI solutions from potential threats and vulnerabilities. Key Responsibilities Application Security : Develop security policies and practices for AI and ML models. Conduct security assessments, code reviews, and threat modeling for AI applications. Implement security measures following OWASP Top 10 guidelines to prevent common vulnerabilities. DevSecOps : Integrate security into CI/CD pipelines to enable automated security testing. Use tools like GitHub Actions, Jenkins , and Terraform to automate infrastructure security checks. Promote secure coding standards and practices across development teams. Data Security : Design and implement data protection mechanisms such as encryption (both at rest and in transit) and data anonymization techniques. Ensure compliance with data privacy regulations such as GDPR and CCPA . Utilize tools like Data Loss Prevention (DLP) and data masking technologies for sensitive data protection. Identity & Access Management (IAM) : Develop and enforce IAM strategies across multi-cloud platforms (AWS, Azure, GCP). Implement Zero Trust Architecture and role-based access controls (RBAC) to safeguard user access. Utilize multi-factor authentication (MFA) and identity federation protocols. AI Security & AI Guardrails : Define AI guardrails to mitigate risks like model drift, bias, adversarial attacks, and unauthorized model access. Implement AI model monitoring tools like LIME , SHAP , and IBM AIF360 for model interpretability and fairness. Promote Responsible AI practices, ensuring ethical AI deployment and compliance with industry standards. Cloud Security : Architect and implement secure cloud environments using AWS, Azure, and GCP services. Leverage cloud-native security tools such as AWS Shield , Azure Security Center , and Google Security Command Center . Conduct regular cloud security audits and vulnerability assessments. Compliance & Governance : Ensure alignment with security and compliance frameworks like NIST , ISO 27001 , and SOC 2 . Lead security audits and penetration testing to identify and mitigate vulnerabilities. Establish security policies and guidelines to ensure organizational compliance. Technical Skills Required 3+ years of experience in Data Privacy,cybersecurity, focusing on AI and cloud security. Hands-on experience with one major cloud (AWS, Azure, or GCP) or preferably multi-cloud security (AWS, Azure, GCP)and AI model governance. Strong knowledge of DevSecOps practices and automated security testing. Proficiency with AI/ML security frameworks and tools for monitoring and securing AI models. Experience with security tools like Burp Suite, OWASP ZAP , and SonarQube . Familiarity with AI ethics, model explainability tools (e.g., LIME , SHAP ), and AI risk management. Strong understanding of Privacy by Design Principle, data privacy regulations (GDPR, CCPA) and data security best practices. Knowledge of identity management solutions and best practices in IAM. Strong knowledge of Data lifecycle management in AI context. Preferred Qualifications Certified Information Systems Security Professional (CISSP) Certified Cloud Security Professional (CCSP) AWS Certified Security - Specialty Azure Security Engineer Associate Certified AI Ethics & Governance Professional Soft Skills Excellent communication skills to collaborate with cross-functional teams, including Data Science, DevOps, and Product Management. Strong analytical and problem-solving abilities. Proven ability to stay updated with the latest security trends, AI regulations, and cloud technologies. Ability to articulate security concepts and practices to both technical and non-technical stakeholders. Nice-to-Have Experience with Machine Learning Operations ( MLOps ) security. Hands-on knowledge of Container Security (Docker, Kubernetes). Familiarity with AI ethics frameworks and AI safety research . Exposure to Responsible AI tools and methodologies.

Our Company: Unify Technologies Our Website: http://unifytech.com/ Linked In: https://www.linkedin.com/company/9206998 Offices in: Hyderabad, Bangalore, Pune, Gurgaon India, and Seattle-USA Industry/Domain: Product Engineering Big Data, Healthcare, Cyber Security, Mobile. Few words about Unify Technologies: Unify a Digital Engineering company. We help our clients by providing Digital Engineering Services to develop high-quality products. We have extensive experience in software product engineering and a successful track record of delivering on aggressive delivery plans without compromising on the quality in Cloud, Mobile, and Data practices. Job Title: Experience : (8-10Yrs) - Remote Work - Full Time - Permanent Role Tech Lead AI/ML for Operational Performance & Risk Prediction Location: Work From Home (India) Duration: Permanent Role Engagement Type: Full-time Immediate Joiners Only Role Overview : We are seeking a hands-on Tech Lead to own the architecture, development, and delivery of AI-driven solutions that analyze operational performance, predict risks, and optimize workforce efficiency. This is a permanent position for someone who thrives on solving complex business problems with AI/ML, leading small agile teams, and delivering measurable results in a client-facing environment. Must-Have Skills & Experience Technical Expertise AI/ML Modeling: Strong experience with XGBoost, LightGBM, and Facebook Prophet (time series forecasting). Proven track record in predictive analytics for operational performance and risk modeling. Hands-on experience in model explainability (e.g., SHAP, LIME). Data Engineering & Integration: Proficiency in Python (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow basics). ETL pipeline development using Azure Data Factory or Apache Airflow. Experience with SQL (PostgreSQL / MySQL / MS SQL Server). Cloud Stack: Azure (Data Lake, Synapse, Machine Learning Studio) must be proficient. Deployment of ML models via Azure ML endpoints or containerized solutions. MLOps & Versioning: GitHub/GitLab CI/CD integration. Model lifecycle management & experiment tracking (MLflow, DVC). Domain Knowledge Understanding of field workforce performance metrics, compliance, and KPI-based vendor evaluation. Ability to design a balanced scorecard mapping operational KPIs to financial outcomes. Leadership & Delivery Minimum 810 years of total experience, with 3+ years in a Tech Lead or Solution Architect role. Experience leading small, agile AI/ML delivery teams (35 engineers). Ability to engage with SMEs and translate business goals into technical deliverables. Strong communication skills for working with both technical and operations stakeholders. Nice-to-Have Skills Experience with synthetic data generation for AI training. Knowledge of audio analytics for operational or maintenance insights. Exposure to open-source RAG frameworks (LangChain, Haystack) for operational intelligence. Familiarity with rules-engine integration (e.g., Drools) for hybrid AI + deterministic logic solutions. Key Responsibilities Lead solution design, architecture, and technical delivery of AI-driven operational insights. Ingest and preprocess historical operational, safety, and financial datasets. Build predictive models for workforce performance, delays, and compliance risks. Implement model explainability for stakeholder trust and adoption. Integrate outputs into an Azure-based environment. Ensure data security and compliance with NDA and IT policies. Conduct knowledge transfer to internal and client teams. Engagement Expectations Immediate joiners only must be ready to start within 5 business days. Availability for daily standups and weekly stakeholder reviews. Flexible to work in overlapping hours with US Pacific Time for stakeholder sync. Good to have: Tier 1 and company candidate

As a Senior Specialist in Software Development (Artificial Intelligence) at Accelya, you will lead the design, development, and implementation of AI and machine learning solutions to tackle complex business challenges. Your expertise in AI algorithms, model development, and software engineering best practices will be crucial in working with cross-functional teams to deliver intelligent systems that optimize business operations and decision-making. Your responsibilities will include designing and developing AI-driven applications and platforms using machine learning, deep learning, and NLP techniques. You will lead the implementation of advanced algorithms for supervised and unsupervised learning, reinforcement learning, and computer vision. Additionally, you will develop scalable AI models, integrate them into software applications, and build APIs and microservices for deployment in cloud environments or on-premise systems. Collaboration with data scientists and data engineers will be essential in gathering, preprocessing, and analyzing large datasets. You will also implement feature engineering techniques to enhance the accuracy and performance of machine learning models. Regular evaluation of AI models using performance metrics and fine-tuning them for optimal accuracy will be part of your role. Furthermore, you will collaborate with business stakeholders to identify AI adoption opportunities, provide technical leadership and mentorship to junior team members, and stay updated with the latest AI trends and research to introduce innovative techniques to the team. Ensuring ethical compliance, security, and continuous improvement of AI systems will also be key aspects of your role. You should hold a Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field, along with at least 5 years of experience in software development focusing on AI and machine learning. Proficiency in AI frameworks and libraries, programming languages such as Python, R, or Java, and cloud platforms for deploying AI models is required. Familiarity with Agile methodologies, data structures, and databases is essential. Preferred qualifications include a Master's or PhD in Artificial Intelligence or Machine Learning, experience with NLP techniques and computer vision technologies, and certifications in AI/ML or cloud platforms. Accelya is looking for individuals who are passionate about shaping the future of the air transport industry through innovative AI solutions. If you are ready to contribute your expertise and drive continuous improvement in AI systems, this role offers you the opportunity to make a significant impact in the industry.,

Role & responsibilities Expertise in supervised, unsupervised, machine learning, deep learning, reinforcement learning, statistics techniques. Proficiency in Python, PyTorch, TensorFlow. Good to have knowledge of Bayesian inference, probability distribution, hypothesis testing, A/B testing, and time series forecasting. Hands-on experience with feature engineering and hyperparameter tuning. Experience with MLflow, Weights & Biases, DVC (Data Version Control). Ability to track model performance across multiple experiments and datasets. End-to-end ML lifecycle management from Data ingestion, preprocessing, feature engineering, model training, deployment, and monitoring. Expertise in CI/CD for ML, containerization (Docker, Kubernetes), and orchestration (Kubeflow). Good to have experience in automating data labelling and feature stores (Feast). Good to have data processing experience in Spark, Flink, Druid, Nifi. Good to have real-time data streaming in Kafka and other messaging systems Designing and optimizing data pipelines for structured data. Good to have hands-on experience with Pyspark. Strong SQL skills for data extraction, transformation, and query optimization. Atleast one database experience such as NOSQL database. Implementing parallel and distributed ML techniques for large-scale systems. Good to have knowledge of model explainability (SHAP, LIME), bias mitigation, and adversarial robustness. Experience in model drift monitoring. Good to have CUDA for GPU acceleration. Good to have choosing between CPU/GPU for different ML workloads (batch inference on CPU, training on GPU). Good to have scaling deep learning models on multi-GPU. Strong presentation skills, including data storytelling, visualization (Matplotlib, Seaborn, Superset), and report writing. Experience in mentoring data scientists, research associates, and data engineers. Contributions to research papers, patents, or open-source projects.

Dear, Greetings from Unify Technologies..!! I hope you are doing well, Im reaching out from Unify Technologies - Hyderabad. We have followed the Job Opportunity at our company, please go through the job details and let us know if you are interested. Our Company: Unify Technologies Our Website: http://unifytech.com/ Linked In: https://www.linkedin.com/company/9206998 Offices in: Hyderabad, Bangalore, Pune, Gurgaon India, and Seattle-USA Industry/Domain: Product Engineering – Big Data, Healthcare, Cyber Security, Mobile. Few words about Unify Technologies: Unify a Digital Engineering company. We help our clients by providing Digital Engineering Services to develop high-quality products. We have extensive experience in software product engineering and a successful track record of delivering on aggressive delivery plans without compromising on the quality in Cloud, Mobile, and Data practices. Job Title: Experience : (3-10Yrs) - Remote Work - Full Time - Permanent Role Tech Lead – AI/ML for Operational Performance & Risk Prediction Location: Work From Home (India) Duration: Permanent Role Engagement Type: Full-time – Immediate Joiners Only Role Overview : We are seeking a hands-on Tech Lead to own the architecture, development, and delivery of AI-driven solutions that analyze operational performance, predict risks, and optimize workforce efficiency. This is a permanent position for someone who thrives on solving complex business problems with AI/ML, leading small agile teams, and delivering measurable results in a client-facing environment. Must-Have Skills & Experience Technical Expertise AI/ML Modeling: Strong experience with XGBoost, LightGBM, and Facebook Prophet (time series forecasting). Proven track record in predictive analytics for operational performance and risk modeling. Hands-on experience in model explainability (e.g., SHAP, LIME). Data Engineering & Integration: Proficiency in Python (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow basics). ETL pipeline development using Azure Data Factory or Apache Airflow. Experience with SQL (PostgreSQL / MySQL / MS SQL Server). Cloud Stack: Azure (Data Lake, Synapse, Machine Learning Studio) – must be proficient. Deployment of ML models via Azure ML endpoints or containerized solutions. MLOps & Versioning: GitHub/GitLab CI/CD integration. Model lifecycle management & experiment tracking (MLflow, DVC). Domain Knowledge Understanding of field workforce performance metrics, compliance, and KPI-based vendor evaluation. Ability to design a balanced scorecard mapping operational KPIs to financial outcomes. Leadership & Delivery Minimum 8–10 years of total experience, with 3+ years in a Tech Lead or Solution Architect role. Experience leading small, agile AI/ML delivery teams (3–5 engineers). Ability to engage with SMEs and translate business goals into technical deliverables. Strong communication skills for working with both technical and operations stakeholders. Nice-to-Have Skills Experience with synthetic data generation for AI training. Knowledge of audio analytics for operational or maintenance insights. Exposure to open-source RAG frameworks (LangChain, Haystack) for operational intelligence. Familiarity with rules-engine integration (e.g., Drools) for hybrid AI + deterministic logic solutions. Key Responsibilities Lead solution design, architecture, and technical delivery of AI-driven operational insights. Ingest and preprocess historical operational, safety, and financial datasets. Build predictive models for workforce performance, delays, and compliance risks. Implement model explainability for stakeholder trust and adoption. Integrate outputs into an Azure-based environment. Ensure data security and compliance with NDA and IT policies. Conduct knowledge transfer to internal and client teams. Engagement Expectations Immediate joiners only – must be ready to start within 5 business days. Availability for daily standups and weekly stakeholder reviews. Flexible to work in overlapping hours with US Pacific Time for stakeholder sync. Kindly reply to this mail with the following details if you are interested in applying for this position to bindumadhurij@unifytech.com Total Experience: Highest Education with Passed Out Year: AI/ML Developer experience: AI/ML Lead / Tech Architect Experience: Python programming experience: AWS or Azure experience: Current Company: If Payroll is other(Mention company name): Current Location: Current CTC: Expected CTC: Notice Period(LWD,pls): Form16 from all Employments(Yes or no): Offer In Hand(with Budget): Reason for Job change: Confirm that you are willing to work at the mentioned job location/ **Reason for relocation**: **Confirm that you have gone through all company details and job details and that you are interested to pursue this role and job, Company*: Attach Updated Resume :