A year ago, OpenAI introduced its generative AI chatbot as a research prototype, and unexpectedly, it became highly sought after in 2023. The demand for generative AI is evident in the doubling of global job postings mentioning AI or generative AI on LinkedIn from July 2021 to July 2023. This aligns with the broader trend in the AI market, projected to grow at an annual rate of 37.3% from 2023 to 2030.
As the year concludes, we’ve compiled a list of promising generative AI jobs for those considering a job switch in January, 2024. Let’s take a look at them.
ML Engineer, MachineHack
Bengaluru-based generative AI startup MachineHack is seeking an adept Project Manager with a strong background in machine learning (ML) to oversee ML projects. The ideal candidate should possess a combination of technical expertise in ML technologies and proficient project management skills.
Responsibilities include leading ML projects, managing teams of data scientists and engineers, utilising platforms such as PyTorch and OpenAI, handling AWS tools for ML solutions, employing Docker for containerization, and facilitating communication between technical and non-technical stakeholders. The role emphasises staying abreast of the latest ML and AI developments and integrating innovative technologies into projects.
The ideal candidate should have a Bachelor’s or Master’s degree in Computer Science or a related field, a minimum of 3 years of project management experience in ML or similar domains, proficiency in relevant technologies, and demonstrated leadership capabilities. Experience in tech-driven or AI-centric companies is preferred.
Apply here.
Generative AI Engineer, Siemens Healthineers
Also located in Bengaluru, Siemens Healthineers is expanding their footprint and is looking for generative AI engineers. The employee will be tasked with developing and implementing cutting-edge generative models and algorithms by leveraging the latest technologies. The role necessitates a profound comprehension of machine learning, neural networks, and various AI techniques.
Responsibilities include researching, designing, and implementing advanced generative models, collaborating with software engineers for model integration, conducting thorough testing, and staying updated on AI and machine learning advancements. Key qualifications for the position include a bachelor’s or master’s degree in computer science or a related field, three to five years of experience as a ML Engineer with a focus on generative AI and neural networks, proficiency in Python, C++, or Java programming, familiarity with deep learning frameworks like TensorFlow or PyTorch, and knowledge of machine learning algorithms and cloud computing platforms such as AWS or Azure.
If you think you are fit for this role, apply here.
Generative AI Common Platform Engineer, Citigroup
Citigroup, a prominent global banking and financial services company, is hiring a Generative AI Common Platform Engineer to contribute to its technological advancement. The role involves developing and maintaining the Generative AI common platform, collaborating on AI solutions, researching and implementing cutting-edge AI technology, and working with data scientists to enhance AI models. The engineer will troubleshoot technical issues, monitor AI model performance, and integrate new technologies into the platform. Compliance with industry standards and risk mitigation are essential, along with training and mentoring team members. Effective communication and continuous improvement of processes are emphasised to drive the future direction of AI at Citigroup.
Check out the job here.
Senior Principal Outbound Solutions Manager, Generative AI Solutions, Oracle Cloud Infrastructure (OCI)
The Senior Principal Outbound Solutions Manager at Oracle, based in Bengaluru, Karnataka, plays a crucial role in the Oracle Cloud Infrastructure (OCI) Generative AI solutions team. This team focuses on expanding OCI’s Generative AI services, aiming to empower customers in solving specific business challenges using Oracle’s Generative AI expertise. The role involves collaborating with data scientists and developers from major Fortune 100 companies to deliver secure and effective solutions.
The person will be working closely with strategic customers, both internal and external, to develop end-to-end Generative AI solutions, addressing gaps in the product portfolio, and fostering collaboration between engineering, product, research, and sales teams. The ideal candidate should possess over 10 years of relevant experience, expertise in key industries, and a growth mindset, with hands-on experience in machine learning and artificial intelligence. The emphasis is on customer focus, narrative building, and effectively bridging the technical-business divide.
Check out the job description for more information.
LLM Engineer, Pure Storage
The LLM Engineer – AI / ML Engineer plays a key role in the enterprise’s transformation through the application of generative AI technologies. The position involves conducting advanced research and experimentation with cutting-edge technologies in generative AI, focusing on the development of custom applications to address complex business challenges.
The role includes leading the development of innovative generative AI solutions, exploring advanced AI models, and architecting robust AI systems that integrate with enterprise IT infrastructure. The role also entails guiding technical project direction, leading and mentoring a team of AI/ML engineers, and collaborating with stakeholders to translate AI/ML concepts into business strategies.
Requirements for the role include extensive experience in AI/ML technologies and software development, expertise in relevant programming languages and tools, proficiency in cloud architectures and data engineering, and leadership skills in managing technical teams and driving innovation.
Apply here.
Lead Generative AI Engineer, Ola
Ola is on the lookout for a skilled lead generative AI engineer who will train, optimise, and deploy various large language models, voice and speech foundation models, and vision models. The engineer will focus on architecting robust infrastructure for model deployment, optimising for low latency, high throughput, and cost efficiency.
Key responsibilities include refining foundation model infrastructure, implementing optimization techniques, leading LLMOps pipeline development, and driving innovation in model deployment platforms. The qualifications sought include a PhD with over five years or an MS with over eight years of experience in ML Engineering, proficiency in Python, C/C++, CUDA, and kernel-level programming, expertise in large-scale AI model optimization, and a track record of deploying ML systems at scale using cloud infrastructures and GPU resources. Strong communication, collaboration, and leadership skills are essential.
Check out their careers page now.
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