A year ago, OpenAI introduced generative AI chatbots as a research prototype that unexpectedly became extremely popular in 2023. The demand for generative AI is evidenced by a doubling of job ads mentioning AI or generative AI worldwide on LinkedIn between July 2021 and July 2023. This is in line with the overall trend of the AI market, which is predicted to grow 37.3% annually from 2023 to 2030.
As the year draws to a close, we’ve compiled a list of promising generative AI-related roles for those considering a career change in January 2024. Let’s dive right in.
ML Engineer, MachineHack
MachineHack, a Bengaluru-based generative AI startup, is seeking a talented Project Manager with extensive experience in Machine Learning (ML) to oversee their ML projects. The ideal candidate should have both technical expertise in ML technologies and excellent project management skills.
Your responsibilities will include leading ML projects, managing a team of data scientists and engineers, leveraging platforms like PyTorch and OpenAI, handling AWS tooling for ML solutions, adopting Docker for containerization, facilitating communication between technical and non-technical stakeholders, etc. In this role, your focus will be on staying up to date with the latest ML and AI developments and integrating innovative technologies into projects.
The ideal candidate will have a Bachelor's or Master's degree in Computer Science or related field, a minimum of 3 years of project management experience in ML or similar field, familiarity with relevant technologies, and demonstrated leadership capabilities. Experience in a technology-driven or AI-centric company is preferred.
Please apply here.
Siemens Healthcare Generative AI Engineer
Siemens Healthineers, also based in Bengaluru, is expanding its footprint and is hiring a Generative AI Engineer. The employee will be tasked with developing and implementing cutting-edge generative models and algorithms leveraging the latest technologies. The role requires a deep understanding of machine learning, neural networks, and various AI techniques.
Your duties will include researching, designing, and implementing advanced generative models, working with software engineers for model integration, performing thorough testing, staying up to date on advancements in AI and machine learning, etc. Key qualifications for this position include a Bachelor's or Master's degree in Computer Science or related field, 3-5 years of experience as an ML engineer with a focus on generative AI and neural networks, proficiency in Python, C++, or Java programming, knowledge of deep learning frameworks such as TensorFlow and PyTorch, knowledge of machine learning algorithms and cloud computing platforms such as AWS and Azure.
If you think you would be a good fit for this role, please apply here.
Generative AI Common Platform Engineer, Citigroup
Citigroup, a global banking and financial services company, is looking for a Generative AI Common Platform Engineer to contribute to technological advancements. This role will involve developing and maintaining the Generative AI Common Platform, collaborating on AI solutions, researching and implementing cutting edge AI techniques, and working with data scientists to enhance AI models. The engineer will troubleshoot technical issues, monitor the performance of AI models, and integrate new technologies into the platform. Adherence to industry standards and risk mitigation are essential along with training and mentoring team members. Effective communication and continuous process improvement are emphasized to drive the future direction of AI at Citigroup.
Check out the job description here.
Sr. Principal Outbound Solutions Manager, Generative AI Solutions, Oracle Cloud Infrastructure (OCI)
Based in Bengaluru, Karnataka, the Sr. Principal Outbound Solutions Manager at Oracle plays a key role in the Oracle Cloud Infrastructure (OCI) Generative AI Solutions team, which is focused on expanding OCI's Generative AI offerings and enabling customers to solve specific business challenges using Oracle's Generative AI expertise. This role involves working with data scientists and developers at leading Fortune 100 companies to deliver secure and effective solutions.
The individual in this role will work closely with internal and external strategic customers to develop end-to-end generative AI solutions, close gaps in the product portfolio, and drive collaboration across engineering, product, research, and sales teams. The ideal candidate will have 10+ years of relevant experience, key industry expertise, growth mindset, and hands-on experience in machine learning and artificial intelligence. Emphasis will be on customer focus, story building, and effectively bridging the gap between technology and business.
Please see the job description for more details.
LLM Engineer, Pure Storage
The LLM Engineer – AI/ML Engineer will play a key role in transforming enterprises through the application of generative AI techniques. This position will involve conducting advanced research and experimentation with cutting edge techniques in generative AI, with a focus on developing custom applications to address complex business challenges.
This role will involve leading the development of innovative generative AI solutions, exploring advanced AI models and designing robust AI systems that integrate with the enterprise IT infrastructure. It will also involve guiding technical project direction, leading and mentoring a team of AI/ML engineers and collaborating with stakeholders to translate AI/ML concepts into business strategy.
Requirements for this role include extensive experience in AI/ML technologies and software development, expertise in relevant programming languages and tools, proficiency in cloud architecture and data engineering, and leadership skills in managing technical teams and driving innovation.
Please apply here.
Lead Generative AI Engineer, Ola
Ola is looking for a skilled Lead Generation AI Engineer to train, optimize, and deploy a variety of large scale Language models, Voice and Speech Foundation models, and Vision models. The Engineer will focus on designing a robust infrastructure for model deployment, optimizing for low latency, high throughput, and cost efficiency.
Key responsibilities will include improving the foundational model infrastructure, implementing optimization techniques, leading LLMOps pipeline development and driving innovation in model deployment platforms. Desired qualifications include 5+ years of PhD or 8+ years of MSc experience in ML engineering, proficiency in Python, C/C++, CUDA, kernel level programming, expertise in large scale AI model optimization, and proven track record of deploying ML systems at scale using cloud infrastructure and GPU resources. Strong communication, collaboration and leadership skills are essential.
Check out their careers page now.
