We are looking for an experienced Machine Learning Engineer to join our team, working on a hybrid basis from our Lucknow office and from home. In this role you will be a key member of our Data Science function, contributing directly to our goals and working closely with talented colleagues across the business.
This is a hands-on role with real ownership and impact. You will apply your skills in Python, PyTorch and MLOps to solve interesting problems, ship work you can be proud of and help us raise the bar for what we do. You will collaborate with cross-functional teams, share your ideas openly and have the support you need to do your best work and grow along the way.
You will bring around 3 to 6 years of relevant experience and strong, practical knowledge of Python, PyTorch and MLOps. Just as important are clear communication, sound judgement, attention to detail and the ability to collaborate effectively with people across different teams and backgrounds.
Within your first few months, you will get up to speed with our products, processes and people, build strong working relationships across the team, and begin taking ownership of your own work. Over time, you will have the opportunity to deepen your expertise, take on broader scope and grow your career with us as the company continues to scale.
In return, we offer a supportive, inclusive and collaborative environment, competitive pay, meaningful benefits and the chance to do work that genuinely matters. We care about our people, invest in their growth and want everyone here to be able to do the best work of their careers.
If this sounds like you, we would love to hear from you. Onyx Systems is an equal-opportunity employer: we welcome applicants of all backgrounds and are committed to building a diverse team and an inclusive workplace where everyone can thrive. Apply today and tell us why you would be a great fit.
Responsibilities
As a Machine Learning Engineer at Onyx Systems, you will play a central role within our Data Science function and take ownership of a broad and varied set of responsibilities. Working alongside a collaborative, motivated team, your day-to-day duties will include, but are not limited to, the following:- Develop, validate and deploy analytical and machine-learning models that turn raw data into actionable business value.
- Collaborate with engineering teams to productionise models and integrate insights into customer-facing features.
- Evaluate new data tools, platforms and techniques, recommending improvements to our data infrastructure.
- Document data sources, definitions and methodologies so insights are trusted and easy to reproduce.
- Define and track the metrics that matter, and proactively surface trends, risks and opportunities to leadership.
- Mentor colleagues on data literacy and help embed a culture of evidence-based decision making.
- Conduct exploratory analysis and experiments, and communicate findings clearly to technical and non-technical audiences.
- Maintain reproducible, version-controlled analysis and follow sound experimental and statistical practices.
- Partner with stakeholders to translate ambiguous business questions into well-defined, measurable analytical problems.
- Build and maintain dashboards, reports and self-serve tools that make data accessible across the organisation.
- Design, build and maintain robust data pipelines that ingest, clean, transform and serve data reliably at scale.
- Ensure data quality, integrity and governance through validation, monitoring, documentation and clear data contracts.
- Continuously develop your skills, seek feedback and stay current with the latest developments in your field.
- Communicate progress, risks and blockers clearly and proactively to your manager and relevant stakeholders.
- Uphold the company's values, policies, security requirements and standards of professional conduct in all activities.
- Adapt to changing priorities and remain calm, focused and effective in a fast-moving, evolving environment.
- Ensure your work meets agreed quality, compliance and security standards before it is considered complete.
- Handle confidential and sensitive information with discretion, care and integrity at all times.
- Participate constructively in team meetings, stand-ups, planning sessions, demos and retrospectives.
- Contribute to a culture of accountability, learning from mistakes and celebrating shared wins.
- Plan and manage your workload to balance quality, speed and competing demands.
- Support and step in for teammates when needed to help the team meet its shared goals.
- Support onboarding, knowledge-sharing and documentation so the wider team can learn, scale and succeed.
- Maintain accurate, thorough documentation and keep all relevant systems, tools and trackers up to date.
- Contribute actively to a positive, inclusive, supportive and collaborative team culture.
- Identify opportunities for improvement and bring forward practical ideas to make our products, processes and ways of working better.
What we're looking for
3-6 years of professional experience in a Machine Learning Engineer or similar roleStrong working knowledge of Python, PyTorch and MLOps
Bachelor's degree in Computer Science
Excellent communication, problem-solving and teamwork skills
Benefits
At Onyx Systems, we believe that looking after our people is the foundation of doing great work. We offer a comprehensive, thoughtfully designed benefits and perks package that supports your health, your finances, your growth and your life outside of work. When you join us, you can expect the following:- Comprehensive medical, dental and vision insurance for you and your dependants, so you and your family are well looked after.
- Provident Fund (PF) contributions and gratuity in line with statutory requirements, helping you build long-term financial security for the future.
- Regular team lunches, celebrations, offsites and social events that make work more fun, human and connected.
- A culture that actively encourages experimentation, stretch projects and learning from both wins and mistakes.
- Employee discounts and access to a curated range of partner perks, offers and benefits.
- A results-focused environment that values outcomes and impact over hours logged at a desk.
- Allowances and reimbursements for work-related expenses, handled quickly and without unnecessary bureaucracy.
- Protected time for learning, regular internal knowledge-sharing sessions and access to leading online learning platforms.
- A competitive salary that is reviewed regularly and benchmarked against the market to keep your pay fair and current.
- Personal accident and term life insurance providing financial protection and peace of mind for you and your loved ones.
- Hybrid and remote-friendly working options, with the trust and autonomy to manage your own time and output.
- Commuter, transport and travel support to make getting to and from work easier and more affordable.
- A flat, low-ego environment where good ideas can come from anyone and are acted upon.
- Company-funded health insurance with access to a wide network of hospitals and clinics, plus an annual preventive health check-up.
- A modern, well-equipped office in a convenient location, with snacks, great coffee and plenty of collaborative space.
- Employee stock options (ESOPs), giving you a genuine stake in the company's growth and long-term success.
- Regular recognition and appreciation for great work, both publicly and privately.
- Recognition of personal milestones with celebration leave and thoughtful gestures.
- Transparent communication, regular all-hands updates and direct, approachable access to leadership.
- earned, casual and sick leave in line with company policy, plus public holidays, because rest and time to recharge are essential to doing great, sustainable work.
- Wellness perks such as gym and fitness-membership support, plus wellbeing initiatives throughout the year.
- Generous, fully paid parental leave for all new parents, supporting you through one of life's biggest moments.
- Additional wellbeing and volunteering days each year to look after yourself and give back to your community.
Education
Bachelor's degree in Computer Science