Our typical workday has changed as a result of generative AI. LLM-based chatbots like Bard and ChatGPT are easing human burdens one cue at a time, from writing emails to creating poetry. Tech businesses are actively hiring to improve current models and create new ones because the effectiveness of these generative AI models depends on their training. More than merely a scientific marvel, generative AI is a key factor in the growth of numerous sectors and the development of new jobs.
Let’s look at some of the best employment options in this area.
ML Engineer at Apple (Generative AI)
The huge IT company began looking for a passionate and committed ML engineer to join their Cloud Technologies App Platform team in Hyderabad not long after the news of AppleGPT broke. The position entails developing and implementing a machine learning strategy to improve Apple’s platform for developers and speed up app development. The ideal applicant should be well-versed in deep learning, statistics, and sophisticated machine learning techniques, as well as have experience with transformer models like BERT, GPT, and Roberta. They will possess strong software development abilities (Python, PyTorch, TensorFlow, JAX), be able to optimize and fine-tune large language models and construct MLOps infrastructure for experimentation, A/B testing, and production deployment.
Experience delivering complicated ML insights to non-technical audiences and working with LangChain pipelines and MLOps tools are highly sought. With an emphasis on enhancing the developer experience, the position seeks to contribute to Apple’s generative AI-based developer platform by working with data scientists and software developers to deliver ML solutions for internal use. The ideal candidate will have at least five years of experience working in the AI/ML-focused software business, as well as the necessary academic credentials (BTech, MTech, MS, or PhD in comparable subjects).
Eli Lilly, Senior Team Lead for Generative AI
To grow its presence in India, the American pharmaceutical corporation Eli Lilly is hiring a generative AI and machine language engineer. To oversee the whole data lifecycle, which includes data collection, cleaning, preprocessing, model training, and production deployment, the position calls for a machine learning specialist. The main duties comprise setting up contemporary Natural Language Technology (NLT) systems to conclude essential company data. This comprises creating, putting into use, and maintaining tools for sophisticated analytics and data preparation, presenting business users with insights from various data sources, and creating language understanding/generation systems employing text representation approaches.
Working with engineering partners to develop the finest cloud-based ML solutions, researching and implementing cutting-edge NLG algorithms for tasks like summarization, and creating the best deployment and infrastructure practices are some of the key duties. The role’s other important responsibilities include preserving the performance of ML models, automating ML model operations, and cultivating connections with diverse stakeholders. Experience in NLP/NLU/NLG, AWS, Python, Java, R coding, MLOps, Docker/Kubernetes familiarity, agile development experience, and designing, developing, and researching ML systems are all prerequisites.
Engineer for generative AI at Siemens Healthineers
An experienced generative AI engineer is needed to join Siemens Healthineers’ research and development team. For a variety of applications, the role entails creating and implementing generative AI models including GANs, VAEs, and Transformers. Data preprocessing, model training, evaluation, deployment, optimization, and cooperation with cross-functional teams are among the responsibilities. Fundamental knowledge of machine learning, programming skills in Python and other programming languages, deep learning experience, data preprocessing skills, software engineering skills, awareness of ethical issues, and a commitment to lifelong learning are essential. In addition, maintaining generative models in production systems, security, documentation, problem-solving, and, if applicable, domain knowledge in the field of healthcare are all part of the work.
Lead Manager at PwC for Generative AI and Data Analytics
To apply cutting-edge analytics and AI approaches to complex business challenges, PwC is looking for a skilled generative AI and data analytics lead manager to join its Kolkata team. To promote innovation and corporate growth, this role requires a blend of technical expertise, strategic thinking, and business acumen. The duties include independently interacting with both domestic and international clients, utilizing a strong mathematical background in statistics and probabilities, working with various teams to identify business priorities, developing predictive and statistical models, utilizing generative AI to improve processes, managing data pipelines, and reporting findings to various stakeholders.
A bachelor’s degree in computer science, statistics, mathematics, or a similar discipline is required as well as 10–12 years of expertise in analytics or artificial intelligence. A master’s or PhD degree is preferred. It is assumed that users will be proficient in statistical modeling, data visualization tools, deep learning frameworks like TensorFlow or PyTorch, Python or R programming, and project management.
Wipro, Architect for Generative AI
An opening for a generative AI architect (C1) is being advertised by Indian IT giant Wipro. It calls for a seasoned expert with at least ten years of experience. In addition to integrating cloud-based generative AII algorithms, the role entails inventing and putting into practice cutting-edge generative AI models and algorithms, such as GPT, VAE, and GANs. It is crucial to work with cross-functional teams to connect AI projects with corporate goals.
Part of the job involves keeping up with the most recent developments in generative AI, machine learning, and deep learning and optimizing current models for improved performance. It is necessary to be proficient in Python, NLP tools like SpaCy, NLTK, and Hugging Face, cloud platforms like AWS, GCP, or Azure, and deep learning frameworks like TensorFlow, PyTorch, or Keras.
Engineer for generative AI, Ascension
You will be in charge of optimizing generative AI models in this position with engineering company Ascendion to make sure they function effectively in a variety of applications. Additionally, building clever AI agents to better user interactions and testing out cutting-edge methods to boost recommender systems will be among your objectives. Building and managing inference pipelines for seamless AI model deployment across various platforms, as well as deployment and versioning management for seamless updates and rollbacks, will fall within your purview.
Additionally, with a heavy emphasis on software engineering principles, you’ll create tools to regularly evaluate model performance in production. You’ll optimize and oversee machine learning models in production scenarios by drawing on your knowledge of transformer models and text embeddings. The position provides flexibility for remote work, chances for skill development, and a range of benefits and prizes.
