software engineer

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software engineer, data engineer ii Jobs in Pune

software engineer, data engineer ii

machine learning engineer

Google

<div>
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 Bengaluru, Karnataka, India; Gurugram, Haryana, India; Hyderabad, Telangana, India; Mumbai, Maharashtra, India; Pune, Maharashtra, India
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent practical experience.
 </li>
 <li>
 Experience working with Unix/Linux environments, distributed systems, machine learning, information retrieval, and TCP/IP.
 </li>
 <li>
 Experience programming in C, C++, Java, or Python.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's or Advanced degree in Computer Science or Computer Engineering, or a related field.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
 
 
 As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.
 
 
 Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Research, conceive, and develop software applications to extend and improve on Google's product offering.
 </li>
 <li>
 Contribute to a wide variety of projects utilizing natural language processing, artificial intelligence, data compression, machine learning, and search technologies.
 </li>
 <li>
 Collaborate on scalability issues involving access to data and information.
 </li>
 <li>
 Solve challenges/problems that you are presented with.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Software Engineer, University Graduate, 2026

Aligned Automation

<div>
 
 
 Job Description:
 
 
 
 
 
 Role Overview:
 
 
 
 
 We are seeking a seasoned ML Engineer with strong MLOps expertise to lead and scale our machine learning infrastructure. The ideal candidate will be responsible for designing, deploying, and maintaining robust ML pipelines, ensuring model reproducibility, scalability, and performance in production environments.
 
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Participate in Agile/Scrum ceremonies and contribute to sprint planning and retrospectives.
 
 </li>
 </ul>
 <ul>
 <li>
 Scope and break down complex ML problems into actionable tasks.
 
 </li>
 </ul>
 <ul>
 <li>
 Write clean, scalable, and production-ready code for ML pipelines and services.
 
 </li>
 </ul>
 <ul>
 <li>
 Design and implement efficient ETL workflows for structured and unstructured data.
 
 </li>
 </ul>
 <ul>
 <li>
 Develop Python scripts for data preprocessing, feature engineering, and automation tasks.
 
 </li>
 </ul>
 <ul>
 <li>
 Submit and manage pull requests; resolve issues flagged by linters/scanners.
 
 </li>
 </ul>
 <ul>
 <li>
 Conduct and participate in code reviews to ensure high-quality standards.
 
 </li>
 </ul>
 <ul>
 <li>
 Collaborate with data scientists, software engineers, and DevOps teams.
 
 </li>
 </ul>
 <ul>
 <li>
 Automate model training, validation, deployment, and monitoring workflows.
 
 </li>
 </ul>
 <ul>
 <li>
 Implement CI/CD pipelines for ML models and data workflows.
 
 </li>
 </ul>
 <ul>
 <li>
 Monitor model performance and data drift in production environments.
 
 </li>
 </ul>
 <ul>
 <li>
 Ensure compliance with data governance and security standards.
 
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Technical Skills:
 
 
 
 <ul>
 <li>
 
 Languages &amp; Frameworks:
 
 Python (advanced), SQL
 
 </li>
 </ul>
 <ul>
 <li>
 
 Data &amp; Storage:
 
 PostgreSQL, S3, data versioning tools
 
 </li>
 </ul>
 <ul>
 <li>
 
 ETL Tools &amp; Practices:
 
 Airflow, Pandas, custom Python-based ETLs
 
 </li>
 </ul>
 <ul>
 <li>
 
 ML &amp; MLOps Tools:
 
 MLFlow (tracking, registry, deployment), LLMs (integration and fine-tuning), Hugging Face, TensorFlow/PyTorch (optional)
 
 </li>
 </ul>
 <ul>
 <li>
 
 Infrastructure &amp; DevOps:
 
 AWS ECS, Docker, Kubernetes (preferred), GitHub Actions
 
 </li>
 </ul>
 <ul>
 <li>
 
 Version Control &amp; Collaboration:
 
 GitHub, GitLab
 
 </li>
 </ul>
 <ul>
 <li>
 
 Monitoring &amp; Logging:
 
 Prometheus, Grafana, or similar tools (optional but preferred)
 </li>
 </ul>
</div>

ML Engineer (MLOPS)

Uplers

<div>
 
 
 Experience:
 
 3 to 7 Years Exp
 
 
 
 Preferred Notice Period:
 
 Upto 30 Days
 
 
 
 Opportunity Type:
 
 Onsite (Pune)
 
 
 
 Placement Type:
 
 Full-time
 
 
 
 (*Note: This is a requirement for one of Uplers' Clients--Newton School)
 
 
 
 
 
 
 
 Must have skills:
 
 AI/ML
 
 and
 
 Deep Learning
 
 and
 
 LLMs
 
 OR
 
 NLP
 
 OR
 
 Transformers
 
 OR
 
 Statistical Modelling
 
 OR
 
 Agentic AI
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Teach Applied AI/ML: Design and deliver practical, project-based courses in AI/ML (Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, GenAI).
 </li>
 <li>
 Develop Industry-Relevant Curriculum: Help design and update the AI/ML curriculum to reflect current industry tools, techniques, and best practices, incorporating your professional experience and case studies.
 </li>
 <li>
 Mentor Student Projects: Guide students through hands-on AI/ML projects, providing technical direction, code reviews, and feedback based on industry standards.
 </li>
 <li>
 Guide &amp; Mentor Students: Advise students on developing practical skills, understanding career paths in AI/ML, and preparing for internships and job placements.
 </li>
 <li>
 Stay Current: Bring the latest AI/ML research, tools, and industry trends into the classroom.
 </li>
 <li>
 Collaborate: Work closely with other expert faculty and staff to create a unified and effective learning experience.
 </li>
 <li>
 Assess Practical Skills: Design and evaluate assignments, projects, and assessments focused on real-world applications.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications &amp; Experience:
 
 
 <ul>
 <li>
 Bachelors or Masters degree in Computer Science, Engineering, Data Science, AI/ML, or related field. (PhD is valued but not mandatory.)
 </li>
 <li>
 3-7 years of direct, hands-on professional experience in the tech industry as an AI/ML Engineer, Data Scientist, Research Scientist, or similar role involving AI/ML development and deployment.
 </li>
 <li>
 Proven Industry Track Record: Demonstrated experience in building, training, and deploying machine learning models (including deep learning) for real-world problems.
 </li>
 <li>
 Deep AI/ML Understanding: Strong grasp of core ML algorithms (classical &amp; deep learning CNNs, RNNs, Transformers), model evaluation, statistics, and awareness of current research/industry trends.
 </li>
 <li>
 Passion for Teaching/Mentoring: Ability to explain complex concepts clearly and guide others. Prior mentoring, corporate training, technical workshops, or project supervision experience is highly relevant. (Formal academic teaching experience is not mandatory.)
 </li>
 </ul>
 
 
 
 
 
 Required Skills:
 
 
 <ul>
 <li>
 Technical: Expert-level Python programming.
 </li>
 <li>
 Proficiency with data science libraries (Pandas, NumPy, Scikit-learn).
 </li>
 <li>
 Hands-on experience with ML/DL frameworks (TensorFlow, PyTorch).
 </li>
 <li>
 Strong SQL and data handling skills.
 </li>
 <li>
 Understanding of ML Ops practices and tools (Git, Docker, AWS/GCP/Azure).
 </li>
 <li>
 Knowledge of key AI areas (NLP, Computer Vision, Generative AI/LLMs).
 </li>
 </ul>
 
 
 
 
 
 Soft Skills:
 
 Strong communication, mentoring ability, collaboration, and a genuine passion for education.
 
 
 
 
 
 
 Good-to-Have
 
 
 <ul>
 <li>
 Prior teaching experience at the undergraduate or graduate level.
 </li>
 <li>
 Familiarity with modern teaching methodologies and academic tools.
 </li>
 </ul>
 
 
 
</div>

Data Scientist

Avantor

<div>
 
 The Opportunity
 
 
 
 A data analyst is responsible for organizing data related to sales numbers, market research, logistics, or other behaviors. They utilize technical expertise to ensure data is accurate and high-quality. Data is then analyzed, designed, and presented in a way that assists individuals, businesses, and organizations make better decisions.
 
 
 
 The Opportunity
 
 
 
 As a Data Scientist, you will leverage advanced statistical methods and machine learning techniques to analyze complex datasets, generate insights, and solve business problems. You will be responsible for developing and deploying ML models, performing deep-dive analyses, and collaborating with stakeholders to ensure the data strategy aligns with business objectives.
 
 
 
 What We're Looking For
 
 
 
 The ideal candidate will be responsible for
 
 
 <ul>
 <li>
 Collect, clean, and analyze large datasets to generate insights and recommendations.
 </li>
 <li>
 Develop and implement machine learning models to solve business problems.
 </li>
 <li>
 Maintain ML pipeline and fix production issues in stipulated time.
 </li>
 <li>
 Work on model maintenance and improvise model performance when necessary.
 </li>
 <li>
 Conduct hypothesis testing and statistical analyses to understand data trends.
 </li>
 <li>
 Communicate findings to non-technical stakeholders through reports and visualizations.
 </li>
 <li>
 Collaborate with engineers, product teams, and business stakeholders to translate business goals into data-driven solutions.
 
 
 </li>
 </ul>
 
 CERTIFICATIONS (Good To Have)
 
 
 
 <ul>
 <li>
 ML/AI certifications
 </li>
 <li>
 Cloud certifications &ndash; like AWS, Azure, GCP etc.
 </li>
 <li>
 Databricks or Snowflake certification.
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in a quantitative field such as Data Science, Statistics, Computer Science, or Engineering.
 </li>
 <li>
 2+ years of experience in working with a product development company as a ML/AI engineer.
 </li>
 <li>
 2+ years of experience and proficiency in programming languages such as Python, Pyspark, Java.
 </li>
 <li>
 Strong hands-on experience in SQL or data manipulation/query language.
 </li>
 <li>
 2+ years of experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
 </li>
 <li>
 Good knowledge on NLP, transformers, LLM and generative AI.
 </li>
 <li>
 Strong analytical skills and proficiency in statistical analysis and data visualization.
 </li>
 <li>
 Good communication and comprehension skills to explain ML algorithms to stakeholders in a non-technical manner.
 </li>
 <li>
 Good Team player and ability to work in cross-functional teams.
 
 
 </li>
 </ul>
 
 How You Will Thrive And Create An Impact
 
 
 
 <ul>
 <li>
 With your analytical mindset and critical thinking, you will have the opportunity to participate in project development activities and suggest data driven and AI based solutions, which will be the foundation of the success of the project.
 </li>
 <li>
 With you proficient coding skills, you will have the opportunity to develop robust ML pipelines which will be modular, scalable and re-usable.
 </li>
 <li>
 You will have the opportunity to work with great minds who focusses on delivering quality products.
 
 
 </li>
 </ul>
 
 Disclaimer
 
 
 
 The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of employees assigned to this position. Avantor is proud to be an equal opportunity employer.
 
 
 
 Why Avantor?
 
 
 
 
 Dare to go further in your career.
 
 Join our global team of 14,000+ associates whose passion for discovery and determination to overcome challenges relentlessly advances life-changing science.
 
 
 
 The work we do changes people's lives for the better.
 
 It brings new patient treatments and therapies to market, giving a cancer survivor the chance to walk his daughter down the aisle. It enables medical devices that help a little boy hear his mom's voice for the first time. Outcomes such as these create unlimited opportunities for you to contribute your talents, learn new skills and grow your career at Avantor.
 
 
 We are committed to helping you on this journey through our diverse, equitable and inclusive culture which includes learning experiences to support your career growth and success. At Avantor, dare to go further and see how the impact of your contributions set science in motion to create a better world.
 
 Apply today!
 
 
 
 
 EEO Statement
 
 
 
 We are an Equal Employment/Affirmative Action employer and VEVRAA Federal Contractor. We do not discriminate in hiring on the basis of sex, gender identity, sexual orientation, race, color, religious creed, national origin, physical or mental disability, protected Veteran status, or any other characteristic protected by federal, state/province, or local law.
 
 
 If you need a reasonable accommodation for any part of the employment process, please contact us by email at recruiting@avantorsciences.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.
 
 
 
 3rd Party Non-solicitation Policy
 
 
 
 By submitting candidates without having been formally assigned on and contracted for a specific job requisition by Avantor, or by failing to comply with the Avantor recruitment process, you forfeit any fee on the submitted candidates, regardless of your usual terms and conditions. Avantor works with a preferred supplier list and will take the initiative to engage with recruitment agencies based on its needs and will not be accepting any form of solicitation
</div>

Deutsche Bank

<div>
 
 Position Overview
 
 
 
 
 Job Title: AI Engineer
 
 
 
 
 Location: Pune, India
 
 
 
 
 Role Description
 
 
 
 Indra is the central program driving the introduction and safe scaling of AI at DB. Focus is identify AI potential across various banking operations, driving funded use cases into production to create value and confidence and scale across the bank, creating selected shared services with embedded safety to enable low cost scale, developing an AI Workbench for developers for safe AI development at pace, and introducing AI controls whilst aiming to maintain time to market.
 
 
 
 What We&rsquo;ll Offer You
 
 
 
 As part of our flexible scheme, here are just some of the benefits that you&rsquo;ll enjoy
 
 
 <ul>
 <li>
 Best in class leave policy
 </li>
 <li>
 Gender neutral parental leaves
 </li>
 <li>
 100% reimbursement under childcare assistance benefit (gender neutral)
 </li>
 <li>
 Sponsorship for Industry relevant certifications and education
 </li>
 <li>
 Employee Assistance Program for you and your family members
 </li>
 <li>
 Comprehensive Hospitalization Insurance for you and your dependents
 </li>
 <li>
 Accident and Term life Insurance
 </li>
 <li>
 Complementary Health screening for 35 yrs. and above
 
 
 
 </li>
 </ul>
 
 Your Key Responsibilities
 
 
 
 <ul>
 <li>
 Model Deployment: Collaborate with data scientists to deploy machine learning models into production environments. Implement deployment strategies such as A/B testing or canary releases to ensure safe and controlled rollouts.
 </li>
 <li>
 Infrastructure Management: Design and manage the infrastructure required for hosting ML models, including cloud resources and on-premises servers. Utilize containerization technologies like Docker to package models and dependencies. Continuous Integration/Continuous Deployment (CI/CD): Develop and maintain CI/CD pipelines for automating the testing, integration, and deployment of ML models. Implement version control to track changes in both code and model artifacts. Monitoring and Logging: Establish monitoring solutions to track the performance and health of deployed models. Set up logging mechanisms to capture relevant information for debugging and auditing purposes.
 </li>
 <li>
 Scalability and Resource Optimization: Optimize ML infrastructure for scalability and cost-effectiveness. Implement auto-scaling mechanisms to handle varying workloads efficiently.
 </li>
 <li>
 Security and Compliance: Enforce security best practices to safeguard both the models and the data they process. Ensure compliance with industry regulations and data protection standards.
 </li>
 <li>
 Data Management: Oversee the management of data pipelines and data storage systems required for model training and inference. Implement data versioning and lineage tracking to maintain data integrity.
 </li>
 <li>
 Collaboration with Cross-Functional Teams: Work closely with data scientists, software engineers, and other stakeholders to understand model requirements and system constraints. Collaborate with DevOps teams to align MLOps practices with broader organizational goals.
 </li>
 <li>
 Performance Optimization: Continuously optimize and fine-tune ML models for better performance. Identify and address bottlenecks in the system to enhance overall efficiency.
 </li>
 <li>
 Documentation: Maintain clear and comprehensive documentation of MLOps processes, infrastructure, and model deployment procedures. Document best practices and troubleshooting guides for the team.
 
 
 
 </li>
 </ul>
 
 Your Skills And Experience
 
 
 
 <ul>
 <li>
 University degree in a technical or quantitative field (e.g., computer science, mathematics, physics, economics, etc.), preferably a Master&rsquo;s or Doctoral degree
 </li>
 <li>
 2-4 years of experience in applying AI, machine learning and/or data science in business and/or academia. Strong knowledge of at least one programming language (e.g., Python, JavaScript) and relevant data science or engineering framework (e.g., scikit-learn, TensorFlow, Spark, etc.).
 </li>
 <li>
 Ideally, practical experience in finance and banking
 </li>
 <li>
 Comfortable working with and managing uncertainty and ambiguity
 </li>
 <li>
 Excellent oral and written communication skills in English
 
 
 
 </li>
 </ul>
 
 How We&rsquo;ll Support You
 
 
 
 <ul>
 <li>
 Training and development to help you excel in your career
 </li>
 <li>
 Coaching and support from experts in your team
 </li>
 <li>
 A culture of continuous learning to aid progression
 </li>
 <li>
 A range of flexible benefits that you can tailor to suit your needs
 
 
 
 </li>
 </ul>
 
 About Us And Our Teams
 
 
 
 Please visit our company website for further information:
 
 
 
 https://www.db.com/company/company.htm
 
 
 
 We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.
 
 
 Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.
 
 
 We welcome applications from all people and promote a positive, fair and inclusive work environment.
</div>

AI Engineer

Oceaneering

<div>
 
 
 Company Profile
 
 
 
 
 Since year 2003, Oceaneering&rsquo;s India Center has been an integral part of operations for Oceaneering&rsquo;s robust product and service offerings across the globe. This center caters to diverse business needs, from oil and gas field infrastructure, subsea robotics to automated material handling &amp; logistics.
 
 
 Our multidisciplinary team offers a wide spectrum of solutions, encompassing Subsea Engineering, Robotics, Automation, Control Systems, Software Development, Asset Integrity Management, Inspection, ROV operations, Field Network Management, Graphics Design &amp; Animation, and more.
 
 
 In addition to these technical functions, Oceaneering India Center plays host to several crucial business functions, including Finance, Supply Chain Management (SCM), Information Technology (IT), Human Resources (HR), and Health, Safety &amp; Environment (HSE).
 
 
 Our world class infrastructure in India includes modern offices, industry-leading tools and software, equipped labs, and beautiful campuses aligned with the future way of work. Oceaneering in India as well as globally has a great work culture that is flexible, transparent, and collaborative with great team synergy.
 
 
 At Oceaneering India Center, we take pride in &ldquo;Solving the Unsolvable&rdquo; by leveraging the diverse expertise within our team. Join us in shaping the future of technology and engineering solutions on a global scale.
 
 
 
 
 Position Summary
 
 
 
 
 The Principal Data Scientist will develop Machine Learning and/or Deep Learning based integrated solutions that address customer needs such as inspection topside and subsea. They will also be responsible for development of machine learning algorithms for automation and development of data analytics programs for Oceaneering&rsquo;s next generation systems.
 
 
 The position requires the Principal Data Scientist to work with various Oceaneering Business units across global time zones but also offers the flexibility to work in a Hybrid Work-office environment.
 
 
 
 
 ESSENTIAL
 
 
 
 
 
 Duties And Responsibilities
 
 
 
 <ul>
 <li>
 Lead and supervise a team of moderately experienced engineers on product/prototype design &amp; development assignments or applications.
 </li>
 <li>
 Work both independently and collaboratively to develop custom data models and algorithms to apply on data sets that will be deployed in existing and new products.
 </li>
 <li>
 Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
 </li>
 <li>
 Assess the effectiveness and accuracy of new data sources and data gathering techniques.
 </li>
 <li>
 Build data models and organize structured and unstructured data to interpret solutions.
 </li>
 <li>
 Prepares data for predictive and prescriptive modeling.
 </li>
 <li>
 Architect solutions by selection of appropriate technology and components
 </li>
 <li>
 Determines the technical direction and strategy for solving complex, significant, or major issues.
 </li>
 <li>
 Plans and evaluates architectural design and identifies technical risks and associated ways to mitigate those risks.
 </li>
 <li>
 Prepares design proposals to reflect cost, schedule, and technical approaches.
 </li>
 <li>
 Recommends test control, strategies, apparatus, and equipment.
 </li>
 <li>
 Develop, construct, test, and maintain architectures.
 </li>
 <li>
 Lead research activities for ongoing government and commercial projects and products. Collaborate on proposals, grants, and publications in algorithm development. Collect data as warranted to support the algorithm development efforts.
 </li>
 <li>
 Work directly with software engineers to implement algorithms into commercial software products.
 </li>
 <li>
 Work with third parties to utilize off the shelf industrial solutions.
 </li>
 <li>
 Algorithm development on key research areas based on client&rsquo;s technical problem. This requires constant paper reading and staying ahead of the game by knowing what is and will be state of the art in this field.
 </li>
 <li>
 Ability to work hands-on in cross-functional teams with a strong sense of self-direction.
 
 
 </li>
 </ul>
 
 
 NON-ESSENTIAL
 
 
 
 
 <ul>
 <li>
 Develop an awareness of programming and design alternatives
 </li>
 <li>
 Cultivate and disseminate knowledge of application development best practices
 </li>
 <li>
 Gather statistics and prepare and write reports on the status of the programming process for discussion with management and/or team members
 </li>
 <li>
 Direct research on emerging application development software products, languages, and standards in support of procurement and development efforts
 </li>
 <li>
 Train, manage and provide guidance to junior staff
 </li>
 <li>
 Perform all other duties as requested, directed or assigned
 
 
 </li>
 </ul>
 
 
 Qualifications
 
 
 
 
 
 REQUIRED
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Electronics and Electrical Engineering (or related field) with eight or more years of past experience working on Machine Learning and Deep Learning based projects
 
 
 </li>
 </ul>
 OR
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Data Science (or related field) with six or more years of past experience working on Machine Learning and Deep Learning based projects
 
 
 </li>
 </ul>
 
 DESIRED
 
 
 
 <ul>
 <li>
 Strong knowledge of advanced statistical functions: histograms and distributions, Regression studies, scenario analysis etc.
 </li>
 <li>
 Proficient in Object Oriented Analysis, Design and Programming
 </li>
 <li>
 Strong background in Data Engineering tools like Python/C#, R, Apache Spark, Scala etc.
 </li>
 <li>
 Prior experience in handling large amount of data that includes texts, shapes, sounds, images and/or videos.
 </li>
 <li>
 Knowledge of SaaS Platforms like Microsoft Fabric, Databricks, Snowflake, h2o etc.
 </li>
 <li>
 Background experience of working on cloud platforms like Azure (ML) or AWS (SageMaker), or GCP (Vertex), etc.
 </li>
 <li>
 Proficient in querying SQL and NoSQL databases
 </li>
 <li>
 Hands on experience with various databases like MySQL/PostgreSQL/Oracle, MongoDB, InfluxDB, TimescaleDB, neo4j, Arango, Redis, Cassandra, etc.
 </li>
 <li>
 Prior experience with at least one probabilistic/statistical ambiguity resolution algorithm
 </li>
 <li>
 Proficient in Windows and Linux Operating Systems
 </li>
 <li>
 Basic understanding of ML frameworks like PyTorch and TensorFlow
 </li>
 <li>
 Basic understanding of IoT protocols like Kafka, MQTT or RabbitMQ
 </li>
 <li>
 Prior experience with bigdata platforms like Hadoop, Apache Spark, or Hive is a plus.
 
 
 </li>
 </ul>
 
 
 Knowledge, Skills, Abilities, And Other Characteristics:
 
 
 
 
 <ul>
 <li>
 Ability to analyze situations accurately, utilizing a variety of analytical techniques in order to make well informed decisions
 </li>
 <li>
 Ability to effectively prioritize and execute tasks in a high-pressure environment
 </li>
 <li>
 Skill to gather, analyze and interpret data.
 </li>
 <li>
 Ability to determine and meet customer needs
 </li>
 <li>
 Ensures that others involved in a project or effort are kept informed about developments and plans
 </li>
 <li>
 Knowledge of communication styles and techniques
 </li>
 <li>
 Ability to establish and maintain cooperative working relationships
 </li>
 <li>
 Skill to prioritize workflow in a changing work environment
 </li>
 <li>
 Knowledge of applicable data privacy practices and laws
 </li>
 <li>
 Strong analytical and problem-solving skills.
 
 
 </li>
 </ul>
 
 
 How To Apply
 
 
 
 
 Oceaneering provides equal employment opportunities to all applicants.
 
 
 
 
 How To Apply
 
 
 
 
 Regular full-time employees who apply will be considered along with external candidates. Employees with less than six months with their current position are not eligible to apply for job postings. Please discuss your interest in the position with your current manager/supervisor prior to submitting your completed application. It is highly recommended to apply through the PeopleSoft or Oceanet portals.
 
 
 
 Closing Statement
 
 
 
 We offer a competitive salary, a comprehensive benefits package and the opportunity to advance in an international company. To apply, click 'Apply Now'.
 
 
 
 
 How To Apply
 
 
 
 
 In addition, we make a priority of providing learning and development opportunities to enable employees to achieve their potential and take charge of their future. As well as developing employees in a specific role, we are committed to lifelong learning and ongoing education, including developing people skills and identifying future supervisors and managers. Every month, hundreds of employees are provided training, including HSE awareness, apprenticeships, entry and advanced level technical courses, management development seminars, and leadership and supervisory training.
 
 
 
 We have a strong ethos of internal promotion. We can offer long-term employment and career advancement across countries and continents.
 
 
 
 Working at Oceaneering means that if you have the ability, drive, and ambition to take charge of your future-you will be supported to do so and the possibilities are endless.
</div>

Principal Data Scientist

<div>
 At EY, you&rsquo;ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we&rsquo;re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
 
 
 
 Job Description: EY GDS &ndash; Data and Analytics - D and A &ndash; Senior &ndash; Senior Data Scientist
 
 
 
 Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.
 
 
 
 Responsibilities:
 
 
 Your technical responsibilities:
 
 
 
 <ul>
 <li>
 Contribute to the design and implementation of state-of-the-art AI solutions.
 </li>
 <li>
 Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
 </li>
 <li>
 Collaborate with stakeholders to identify business opportunities and define AI project goals.
 </li>
 <li>
 Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
 </li>
 <li>
 Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
 </li>
 <li>
 Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
 </li>
 <li>
 Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
 </li>
 <li>
 Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
 </li>
 <li>
 Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
 </li>
 <li>
 Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
 </li>
 <li>
 Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
 </li>
 <li>
 Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
 </li>
 <li>
 Ensure compliance with data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
 
 
 </li>
 </ul>
 
 Requirements
 
 :
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
 </li>
 <li>
 Minimum 3-7 years of experience in Data Science and Machine Learning.
 </li>
 <li>
 In-depth knowledge of machine learning, deep learning, and generative AI techniques.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
 </li>
 <li>
 Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
 </li>
 <li>
 Familiarity with computer vision techniques for image recognition, object detection, or image generation.
 </li>
 <li>
 Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
 </li>
 <li>
 Expertise in data engineering, including data curation, cleaning, and preprocessing.
 </li>
 <li>
 Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
 </li>
 <li>
 Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
 </li>
 <li>
 Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
 </li>
 <li>
 Understanding of data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Track record of driving innovation and staying updated with the latest AI research and advancements.
 
 
 </li>
 </ul>
 
 Good to Have Skills:
 
 
 
 <ul>
 <li>
 Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
 </li>
 <li>
 Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
 </li>
 <li>
 Implement CI/CD pipelines for streamlined model deployment and scaling processes.
 </li>
 <li>
 Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
 </li>
 <li>
 Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
 </li>
 <li>
 Implement monitoring and logging tools to ensure AI model performance and reliability.
 </li>
 <li>
 Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
 </li>
 <li>
 Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.
 
 
 </li>
 </ul>
 
 EY | Building a better working world
 
 
 
 EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
 
 
 Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
 
 
 Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
</div>

EY - GDS Consulting - AI and DATA -Gen AI - Manager

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EY - GDS Consulting - AI and DATA -Gen AI - Manager